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advisor - data architect, data foundry

data architect data foundry

Information Technology Senior Management Forum

<div><div>Posted Date
3/18/2026
</div><div>Description
<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.
Position: Data Architect, Data Foundry
Location: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN
Overview
Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.
Data Foundry is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation &amp; Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities&mdash;serving both human scientists and autonomous AI agents.
Position Summary
We are seeking Data Architects at multiple levels to design and build the data infrastructure that makes AI-native drug discovery possible. You will create the schemas, ontologies, data models, knowledge graphs, and platform architectures that transform raw scientific data into machine-actionable, FAIR-compliant, insight-ready assets&mdash;serving both discovery scientists and autonomous AI agents.
This role is the foundation of Architecture4Insight . Everything the software engineering team builds&mdash;pipelines, APIs, prototypes&mdash;depends on the data models and platform architecture this team designs. You will work with deep knowledge of scientific data (chemical, biological, HTE, automation-generated) to create custom-fit solutions, then partner with Tech@Lilly to scale and maintain them. The role spans three focus areas depending on expertise: data modeling &amp; ontologies , data platform &amp; lakehouse architecture , and knowledge graph &amp; specialized data systems .
Responsibilities
Data Modeling &amp; Ontologies
<ul><li>Design and implement data models, schemas, and ontologies for chemical, biological, and automation-generated data that serve discovery workflows across the portfolio.</li>
<li>Define and maintain controlled vocabularies, metadata standards, and FAIR-compliant data frameworks in partnership with Preparedness4Insight.</li>
<li>Implement semantic data standards (RDF, OWL, SPARQL) and ontology engineering practices to create interoperable, machine-readable scientific data.</li>
</ul>
Data Platform &amp; Lakehouse Architecture
<ul><li>Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent), including data storage patterns, partitioning strategies, and query optimization.</li>
<li>Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools to transform raw scientific data into analytical and ML-ready formats.</li>
<li>Implement real-time and streaming data integration (Kafka, Kinesis, event-driven patterns) connecting LIMS, instruments, and lab automation systems to the data infrastructure.</li>
</ul>
Knowledge Graph &amp; Specialized Data Systems
<ul><li>Design and implement knowledge graphs (Neo4j, Amazon Neptune, TigerGraph) that capture molecular, target, pathway, and experimental relationships across the discovery landscape.</li>
<li>Architect specialized data solutions: array databases (TileDB) for genomics/imaging, document stores (MongoDB) for experimental records, and vector databases for embedding-based retrieval supporting ML and RAG workflows.</li>
<li>Build query and traversal patterns that enable scientists and AI agents to ask relational questions across the entire data landscape.</li>
</ul>
Cross-Functional Partnership
<ul><li>Partner with scientific software engineers to ensure data architectures are implementable, performant, and well-documented.</li>
<li>Collaborate with Methods4Insight to design data structures that support analytical model training, deployment, and evaluation.</li>
<li>Work with Tech@Lilly to define scaling strategies, ensure enterprise compliance, and transition data architectures to production-grade management.</li>
<li>Contribute to build-versus-buy-versus-adopt decisions by evaluating commercial and open-source data platforms against Data Foundry requirements.</li>
</ul>
Basic Requirements
<ul><li>B.S. or M.S. in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field; Ph.D. valued for ontology and knowledge graph roles.</li>
<li>B.S. with 7+ years and M.S. with 5+ years of data architecture, data engineering, or scientific informatics' experience.</li>
<li>SQL skills and experience in multiple database paradigms (relational, graph, document, columnar, key-value).</li>
</ul>
Preferred Qualifications
<ul><li>Expertise in at least one of: data modeling/ontologies, data platform engineering (Databricks, Snowflake, Spark), or graph/specialized databases (Neo4j, Neptune, MongoDB).</li>
<li>Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data integration patterns.</li>
<li>Understanding of scientific data types and experimental workflows in life sciences or pharma (chemical, biological, HTE data).</li>
<li>Strong communication skills with ability to translate data architecture concepts for both technical and scientific audiences.</li>
<li>Pharmaceutical or biotech research industry experience, particularly in discovery data management or research informatics.</li>
<li>Experience with semantic web technologies: RDF, OWL, SPARQL, Prot&eacute;g&eacute;, or equivalent ontology engineering tools.</li>
<li>Hands-on experience with graph databases (Neo4j, Neptune, TigerGraph) and knowledge graph design patterns for scientific data.</li>
<li>Data lakehouse architecture experience: Databricks (Delta Lake, Unity Catalog), Snowflake, or equivalent; ETL/ELT with Spark, dbt.</li>
<li>Experience with streaming/real-time data platforms (Kafka, Kinesis, Flink) and event-driven architectures.</li>
<li>Familiarity with LIMS, ELN systems (e.g., Benchling), and laboratory instrument data integration.</li>
<li>Experience with vector databases (Pinecone, Weaviate, pgvector) and embedding-based retrieval for ML/RAG applications.</li>
<li>Array database experience (TileDB, Zarr) for genomics, imaging, or high-dimensional scientific data.</li>
<li>Experience with bioinformatics data formats (FASTA, BAM/CRAM, VCF) and biological sequence databases; familiarity with NGS data pipelines and proteomics data management.</li>
<li>FAIR data principles implementation experience and Data Readiness Level frameworks.</li>
<li>Scientific data standards and controlled vocabularies in chemistry (InChI, SMILES) or biology (Gene Ontology, UniProt, pathway databases such as Reactome or KEGG).</li>
</ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form ( https://careers.lilly.com/us/en/workplace-accommodation ) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$132,000 - $193,600
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>
</div><div>Salary
132,000.00 - 193,600.00 Annual</div></div><div></div>

Data Architect, Data Foundry

Eli Lilly

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.<h2 class="jobSectionHeader">
Position: Data Architect, Data Foundry</h2>
Location: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN<h1 class="jobSectionHeader">
Overview</h1>
Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.
Data Foundry is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation &amp; Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities&mdash;serving both human scientists and autonomous AI agents.<h1 class="jobSectionHeader">
Position Summary</h1>
We are seeking Data Architects at multiple levels to design and build the data infrastructure that makes AI-native drug discovery possible. You will create the schemas, ontologies, data models, knowledge graphs, and platform architectures that transform raw scientific data into machine-actionable, FAIR-compliant, insight-ready assets&mdash;serving both discovery scientists and autonomous AI agents.
This role is the foundation of Architecture4Insight. Everything the software engineering team builds&mdash;pipelines, APIs, prototypes&mdash;depends on the data models and platform architecture this team designs. You will work with deep knowledge of scientific data (chemical, biological, HTE, automation-generated) to create custom-fit solutions, then partner with Tech@Lillyto scale and maintain them. The role spans three focus areas depending on expertise: data modeling &amp; ontologies, data platform &amp; lakehouse architecture, and knowledge graph &amp; specialized data systems.<h1 class="jobSectionHeader">
Responsibilities</h1><h2 class="jobSectionHeader">
Data Modeling &amp; Ontologies</h2><ul><li>
Design and implement data models, schemas, and ontologies for chemical, biological, and automation-generated data that serve discovery workflows across the portfolio.</li><li>
Define and maintain controlled vocabularies, metadata standards, and FAIR-compliant data frameworks in partnership with Preparedness4Insight.</li><li>
Implement semantic data standards (RDF, OWL, SPARQL) and ontology engineering practices to create interoperable, machine-readable scientific data.</li></ul><h2 class="jobSectionHeader">
Data Platform &amp; Lakehouse Architecture</h2><ul><li>
Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent), including data storage patterns, partitioning strategies, and query optimization.</li><li>
Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools to transform raw scientific data into analytical and ML-ready formats.</li><li>
Implement real-time and streaming data integration (Kafka, Kinesis, event-driven patterns) connecting LIMS, instruments, and lab automation systems to the data infrastructure.</li></ul><h2 class="jobSectionHeader">
Knowledge Graph &amp; Specialized Data Systems</h2><ul><li>
Design and implement knowledge graphs (Neo4j, Amazon Neptune, TigerGraph) that capture molecular, target, pathway, and experimental relationships across the discovery landscape.</li><li>
Architect specialized data solutions: array databases (TileDB) for genomics/imaging, document stores (MongoDB) for experimental records, and vector databases for embedding-based retrieval supporting ML and RAG workflows.</li><li>
Build query and traversal patterns that enable scientists and AI agents to ask relational questions across the entire data landscape.</li></ul><h2 class="jobSectionHeader">
Cross-Functional Partnership</h2><ul><li>
Partner with scientific software engineers to ensure data architectures are implementable, performant, and well-documented.</li><li>
Collaborate with Methods4Insight to design data structures that support analytical model training, deployment, and evaluation.</li><li>
Work with Tech@Lilly to define scaling strategies, ensure enterprise compliance, and transition data architectures to production-grade management.</li><li>
Contribute to build-versus-buy-versus-adopt decisions by evaluating commercial and open-source data platforms against Data Foundry requirements.</li></ul><h1 class="jobSectionHeader">
Basic Requirements</h1><ul><li>
B.S. or M.S. in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field; Ph.D. valued for ontology and knowledge graph roles.</li><li>
B.S. with 7+ years and M.S. with 5+ years of data architecture, data engineering, or scientific informatics' experience.</li><li>
SQL skills and experience in multiple database paradigms (relational, graph, document, columnar, key-value).</li><li>
Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Expertise in at least one of: data modeling/ontologies, data platform engineering (Databricks, Snowflake, Spark), or graph/specialized databases (Neo4j, Neptune, MongoDB).</li><li>
Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data integration patterns.</li><li>
Understanding of scientific data types and experimental workflows in life sciences or pharma (chemical, biological, HTE data).</li><li>
Strong communication skills with ability to translate data architecture concepts for both technical and scientific audiences.</li><li>
Pharmaceutical or biotech research industry experience, particularly in discovery data management or research informatics.</li><li>
Experience with semantic web technologies: RDF, OWL, SPARQL, Prot&eacute;g&eacute;, or equivalent ontology engineering tools.</li><li>
Hands-on experience with graph databases (Neo4j, Neptune, TigerGraph) and knowledge graph design patterns for scientific data.</li><li>
Data lakehouse architecture experience: Databricks (Delta Lake, Unity Catalog), Snowflake, or equivalent; ETL/ELT with Spark, dbt.</li><li>
Experience with streaming/real-time data platforms (Kafka, Kinesis, Flink) and event-driven architectures.</li><li>
Familiarity with LIMS, ELN systems (e.g., Benchling), and laboratory instrument data integration.</li><li>
Experience with vector databases (Pinecone, Weaviate, pgvector) and embedding-based retrieval for ML/RAG applications.</li><li>
Array database experience (TileDB, Zarr) for genomics, imaging, or high-dimensional scientific data.</li><li>
Experience with bioinformatics data formats (FASTA, BAM/CRAM, VCF) and biological sequence databases; familiarity with NGS data pipelines and proteomics data management.</li><li>
FAIR data principles implementation experience and Data Readiness Level frameworks.</li><li>
Scientific data standards and controlled vocabularies in chemistry (InChI, SMILES) or biology (Gene Ontology, UniProt, pathway databases such as Reactome or KEGG).</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$132,000 - $193,600
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.
Location: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN<h2 class="jobSectionHeader">
Reports to: Lead, Data Architecture (R9), Architecture4Insight</h2><h1 class="jobSectionHeader">
Overview</h1>
Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.
Data Foundry is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation &amp; Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities&mdash;serving both human scientists and autonomous AI agents.<h1 class="jobSectionHeader">
Position Summary</h1>
We are seeking Data Architects at multiple levels to design and build the data infrastructure that makes AI-native drug discovery possible. You will create the schemas, ontologies, data models, knowledge graphs, and platform architectures that transform raw scientific data into machine-actionable, FAIR-compliant, insight-ready assets&mdash;serving both discovery scientists and autonomous AI agents.
This role is the foundation of Architecture4Insight. Everything the software engineering team builds&mdash;pipelines, APIs, prototypes&mdash;depends on the data models and platform architecture this team designs. You will work with deep knowledge of scientific data (chemical, biological, HTE, automation-generated) to create custom-fit solutions, then partner with Tech@Lilly to scale and maintain them. The role spans three focus areas depending on expertise: data modeling &amp; ontologies, data platform &amp; lakehouse architecture, and knowledge graph &amp; specialized data systems. You will independently design schemas, select technologies, and make build-vs-buy recommendations for their domain.<h1 class="jobSectionHeader">
Responsibilities</h1><h2 class="jobSectionHeader">
Data Modeling &amp; Ontologies</h2><ul><li>
Design and implement data models, schemas, and ontologies for chemical, biological, and automation-generated data that serve discovery workflows across the portfolio.</li><li>
Define and maintain controlled vocabularies, metadata standards, and FAIR-compliant data frameworks in partnership with Preparedness4Insight.</li><li>
Implement semantic data standards (RDF, OWL, SPARQL) and ontology engineering practices to create interoperable, machine-readable scientific data.</li></ul><h2 class="jobSectionHeader">
Data Platform &amp; Lakehouse Architecture</h2><ul><li>
Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent), including data storage patterns, partitioning strategies, and query optimization.</li><li>
Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools to transform raw scientific data into analytical and ML-ready formats.</li><li>
Implement real-time and streaming data integration (Kafka, Kinesis, event-driven patterns) connecting LIMS, instruments, and lab automation systems to the data infrastructure.</li></ul><h2 class="jobSectionHeader">
Knowledge Graph &amp; Specialized Data Systems</h2><ul><li>
Design and implement knowledge graphs (Neo4j, Amazon Neptune, TigerGraph) that capture molecular, target, pathway, and experimental relationships across the discovery landscape.</li><li>
Architect specialized data solutions: array databases (TileDB) for genomics/imaging, document stores (MongoDB) for experimental records, and vector databases for embedding-based retrieval supporting ML and RAG workflows.</li><li>
Build query and traversal patterns that enable scientists and AI agents to ask relational questions across the entire data landscape.</li></ul><h2 class="jobSectionHeader">
Cross-Functional Partnership</h2><ul><li>
Partner with scientific software engineers to ensure data architectures are implementable, performant, and well-documented.</li><li>
Collaborate with Methods4Insight to design data structures that support analytical model training, deployment, and evaluation.</li><li>
Work with Tech@Lilly to define scaling strategies, ensure enterprise compliance, and transition data architectures to production-grade management.</li><li>
Contribute to build-versus-buy-versus-adopt decisions by evaluating commercial and open-source data platforms against Data Foundry requirements.</li></ul><h1 class="jobSectionHeader">
Basic Requirements</h1><ul><li>
M.S. or Phd in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field</li><li>
6&ndash;12+ years of data architecture, data engineering, or scientific informatics experience.</li><li>
Deep expertise in at least one of the focus areas: relational databases, data modeling and ontology engineering, data platform and lakehouse architecture (Databricks, Snowflake, Spark), or knowledge graph and specialized database systems (Neo4j, Neptune, MongoDB, TileDB)</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Working familiarity with multiple database paradigms &mdash; relational, graph, document, columnar, key-value &mdash; and strong SQL skills.</li><li>
Understanding of scientific data types and experimental workflows in life sciences or pharma (chemical, biological, HTE data).</li><li>
Strong communication skills with ability to translate data architecture concepts for both technical and scientific audiences.</li><li>
Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data integration patterns.</li><li>
Pharmaceutical or biotech research industry experience, particularly in discovery data management or research informatics.</li><li>
Experience with semantic web technologies: RDF, OWL, SPARQL, Prot&eacute;g&eacute;, or equivalent ontology engineering tools.</li><li>
Hands-on experience with graph databases (Neo4j, Neptune, TigerGraph) and knowledge graph design patterns for scientific data.</li><li>
Data lakehouse architecture experience: Databricks (Delta Lake, Unity Catalog), Snowflake, or equivalent; ETL/ELT with Spark, dbt.</li><li>
Experience with streaming/real-time data platforms (Kafka, Kinesis, Flink) and event-driven architectures.</li><li>
Familiarity with LIMS, ELN systems (e.g., Benchling), and laboratory instrument data integration.</li><li>
Experience with vector databases (Pinecone, Weaviate, pgvector) and embedding-based retrieval for ML/RAG applications.</li><li>
Array database experience (TileDB, Zarr) for genomics, imaging, or high-dimensional scientific data.</li><li>
FAIR data principles implementation experience and Data Readiness Level frameworks.</li><li>
Scientific data standards and controlled vocabularies in chemistry (InChI, SMILES) or biology (Gene Ontology, UniProt).</li><li>
Experience with C, C++, or Rust for performance-critical data processing; familiarity with HPC data I/O patterns for large-scale scientific computations.</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$151,500 - $222,200
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

Advisor - Data Architect, Data Foundry

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.
Locations: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN 
Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.
Data Foundry is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation &amp; Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities&mdash;serving both human scientists and autonomous AI agents.
Position Summary
We are seeking an Engineer - MLOps &amp; Scientific Platforms - Data Foundry to operationalize Data Foundry&rsquo;s scientific tools and analytical methods into actionable-prototypes. You will build the ML deployment pipelines, model serving infrastructure, API layers, and observability guardrails that make our scientific discovery methods and tools reliable, scalable, and consumable, both by discovery scientists and by the Frontier AI group&rsquo;s autonomous agents.
This role sits at the interface between Methods4Insight (which develops analytical methods) and Architecture4Insight(which provides the agile data infrastructure). Your job is to ensure every scientific tool Data Foundry produces are analytics-ready, well-monitored, and exposed through APIs with the response-time guarantees and error handling that both human users and AI agents require.
Responsibilities<h2 class="jobSectionHeader">
MLOps &amp; Model Lifecycle Management</h2><ul><li>
Build and maintain end-to-end ML deployment pipelines: experiment tracking, model versioning (MLflow, Weights &amp; Biases), containerized model serving, and automated retraining triggers.</li><li>
Develop model registry infrastructure and feature engineering pipelines that enable computational scientists to access models.</li><li>
Implement monitoring and alerting for data pipelines, APIs, ML models, and agentic systems (LLMOps) to ensure system reliability and performance at scale.</li><li>
Build dashboards and metrics tracking for pipeline execution, API latency, token usage, model prediction quality, and system health</li><li>
Establish structured logging and tracing infrastructure for debugging and performance optimization across scientific data systems</li></ul><h2 class="jobSectionHeader">
Scientific Tool Agile Deployment</h2><ul><li>
Deploy predictive and analytical methods from Methods4Insight (e.g. cheminformatics, structural biology, bioinformatics, reaction informatics) with versioning, structured error handling, and response-time guarantees that enable insight generation in agile manner. Productionize when and where needed in partnerships with Tech@Lilly.</li><li>
Build serving infrastructure supporting both synchronous (interactive scientist queries) and asynchronous (batch and agent-invoked) workloads in partnership with Tech@Lilly and Frontier AI.</li><li>
Define and implement API contracts, documentation standards, and testing frameworks that ensure scientific tools are analysis ready, robust and consumable by external teams including Frontier AI.</li></ul><h2 class="jobSectionHeader">
Platform Engineering &amp; Integration</h2><ul><li>
Build and operate cloud-native model serving infrastructure (AWS, Azure, or GCP) using containers, Kubernetes, and infrastructure-as-code.</li><li>
Develop CI/CD pipelines for ML models: automated validation, A/B testing, canary deployments, and rollback procedures.</li><li>
Integrate model serving with Data Foundry&rsquo;s data pipelines, ensuring models have access to properly formatted, versioned training and inference data.</li></ul><h2 class="jobSectionHeader">
Frontier AI Interface &amp; Collaboration</h2><ul><li>
Partner with the Frontier AI team and Tech@Lilly to ensure Data Foundry&rsquo;s scientific tools are exposed via well-defined interfaces (REST APIs, MCP-compatible endpoints) that agents can invoke programmatically.</li><li>
Collaborate on API performance requirements: latency targets, throughput guarantees, and graceful degradation under load.</li><li>
Work with Methods4Insight scientists to ensure deployed models include appropriate uncertainty quantification and confidence metrics.</li></ul>
Basic Requirements<ul><li>
B.S. or M.S. in Computer Science, Data Science, Machine Learning, Bioinformatics, Computational Biology, or related field.</li><li>
3+ years of experience in MLOps, ML engineering, or scientific platform development</li><li>
Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.</li></ul>
Preferred Qualifications<ul><li>
Pharmaceutical or biotech research industry experience.</li><li>
Strong Python skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and ML lifecycle tools (MLflow, W&amp;B, Kubeflow, or similar).</li><li>
Proven track record building and deploying production model serving infrastructure &mdash; containerized endpoints, RESTful/gRPC APIs, and operational monitoring</li><li>
Working knowledge of cloud platforms (AWS, Azure, or GCP), Kubernetes, and CI/CD automation.</li><li>
Strong communication skills with ability to collaborate across computational scientists, software engineers, and partner teams.</li><li>
Experience operationalizing scientific or computational models (cheminformatics, bioinformatics, structural biology, QSAR, molecular simulations, PK/PD, systems biology, or ODE-based models).</li><li>
Hands-on experience with model monitoring, drift detection, and automated retraining systems.</li><li>
Familiarity with API gateway patterns, event-driven architectures, and service mesh technologies.</li><li>
Experience with feature stores, data versioning (DVC), or experiment tracking at scale.</li><li>
Exposure to AI agent frameworks (MCP, LangChain) or building APIs that AI systems invoke programmatically.</li><li>
Experience with C, C++, CUDA, or GPU-accelerated computing for optimizing model training/inference performance; familiarity with containerizing HPC workloads (Singularity/Apptainer).</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$66,000 - $165,000
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

Engineer - MLOps & Scientific Platforms - Data Foundry

ROLLER

<div>
 
 About ROLLER
 
 
 
 ROLLER is not your average software-as-a-service company. With a global presence in over 30 countries, we're here to bring some excitement to the leisure and attractions industry and make a difference! Our mission is to help businesses operate smoothly and create fun and memorable guest experiences by providing seamless ticketing, point-of-sale, self-serve kiosks, memberships and digital waiver processes.
 
 
 But here's the best part: our team. We're a group of 300+ highly passionate, enthusiastic, and down-to-earth professionals located all around the world who are all working together to build something truly remarkable. We're aiming high and believe that the possibilities are endless. As we continue to grow globally, we're excited to write our success story and have fun along the way.
 
 
 We genuinely love what we do, and we're looking for like-minded people to join us on this amazing journey. If you're ready to be part of a dynamic team and make a real impact, come aboard, and let's create some unforgettable experiences together at ROLLER!
 
 
 
 About the Role
 
 
 
 We are seeking a highly technical, hands-on
 
 Senior
 
 
 Data Engineer
 
 to architect and scale our data infrastructure from the ground up. As a core member of the data function within our Business Technology team, you will be responsible for building the pipelines and models that power smarter decision-making and operational efficiency across the entire organization.
 
 
 In this foundational role, you will build &amp; architect the
 
 modern data stack
 
 , ensuring our infrastructure is robust, automated, and governed. You collaborate as a technical partner with
 
 GTM
 
 
 ,Product, Finance, P&amp;C
 
 to build high-performance data models and pipelines that transform raw data into actionable cross-functional insights.
 
 
 Joining ROLLER at this pivotal growth stage, you will have the opportunity to make an outsized impact on our technical landscape, directly influencing how we process data to deliver world-class experiences for our customers globally.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 
 Scalable Architecture:
 
 Design and implement robust Data Modeling and Architecture strategies that support high-volume data processing and maintain long-term scalability.
 </li>
 <li>
 
 Cloud Ecosystem:
 
 Develop and manage end-to-end data pipelines using Google Cloud Platform services, specifically leveraging Cloud Run, Cloud Function for compute, BigQuery for storage, and Cloud Composer (Airflow) for orchestration.
 </li>
 <li>
 
 Transformation Excellence:
 
 Build, maintain, and document complex data transformation layers using DBT (Data Build Tool) to ensure high data quality and reliability.
 </li>
 <li>
 
 Infrastructure as Code:
 
 Automate the provisioning of cloud resources using Terraform and streamline deployment workflows via GitHub Actions CI/CD pipelines.
 </li>
 <li>
 
 Cloud Data Warehousing:
 
 Demonstrate expert-level proficiency in managing and optimizing Cloud Data Warehouses, such as Snowflake &amp; BigQuery.
 </li>
 <li>
 
 Team Collaboration:
 
 Partner with cross-functional stakeholders to build and scale high-performing data infrastructure that supports engineering, analytics, and Data Program needs.
 </li>
 <li>
 
 Stack Management:
 
 Architect and maintain a modern data stack by implementing best-in-class tools including Snowflake, Bigquery, dbt, Fivetran, Looker, Tableau and Airflow.
 </li>
 <li>
 
 Pipeline Engineering:
 
 Develop scalable ETL/ELT workflows and robust data models to deliver real-time analytics and unified business reporting.
 </li>
 <li>
 
 Data Visualization: Create and maintain intuitive, high-performance Looker dashboards will be an added advantage.
 
 
 
 </li>
 </ul>
 
 About You
 
 
 
 You are a technical builder who views data as a competitive advantage. You thrive in fast-paced environments and have a proven track record of engineering scalable data foundations from the ground up. Equal parts
 
 architect and analytical problem-solver
 
 , you excel at balancing long-term technical vision with the daily hands-on execution of complex pipelines.
 
 
 You are energized by the full lifecycle of data&mdash;moving beyond just writing code to actively leading
 
 project discovery and analysis
 
 alongside cross-functional partners. You take pride in enabling GTM, Product, Finance &amp; P&amp;C teams through clear insights and high-performance systems. Most importantly, you are excited to act as a founding technical force for a high-growth SaaS company that is transforming the guest experience for attractions businesses globally.
 
 
 <ul>
 <li>
 
 5+ years of experience
 
 in Data &amp; Analytics or Data Engineering with a focus on Scalable cloud driven data pipeline build
 </li>
 <li>
 Proven experience in dimensional modeling (Star/Snowflake schema) and designing architectures that support both historical reporting and real-time needs.
 </li>
 <li>
 Expert-level proficiency in Snowflake or BigQuery, including performance tuning, cost optimization, and access control (RBAC).
 </li>
 <li>
 Hands-on experience with Google Cloud Platform services, specifically Cloud Function, Cloud Run for containerized workloads and Cloud Composer for orchestration.
 </li>
 <li>
 Through hands-on experience of dbt (Data Build Tool) to manage transformations, including writing custom macros, implementing tests, and generating documentation.
 </li>
 <li>
 Solid experience using Terraform to provision cloud resources, ensuring that infrastructure is version-controlled and reproducible.
 </li>
 <li>
 Proficiency in GitHub Actions to automate testing and deployment pipelines for data models and infrastructure.
 </li>
 <li>
 Ability to design high-performance dashboards that prioritize user experience and fast load times.
 </li>
 <li>
 Experience collaborating with Finance, GTM, and Product to define key metrics (like CAC, LTV, or Churn) and codifying them into the data layer.
 </li>
 <li>
 Familiarity with data ingestion tools like Fivetran , Airbyte, Workato, Mulesoft to sync data from various SaaS platforms into the warehouse.
 </li>
 <li>
 Operates as a full-stack Data Engineer with the technical authority to architect and build entire data lifecycles, from raw source ingestion to high-impact data visualization.
 </li>
 <li>
 
 Familiarity with business-critical systems
 
 like Salesforce, Chargbee, Gainsight, and product analytics tools.
 </li>
 <li>
 
 Strong communicator
 
 with a track record of working across technical and non-technical teams to drive alignment.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience partnering with IT or Business Technology teams to drive cross-functional outcomes.
 </li>
 <li>
 Exposure to customer success and revenue workflows, such as onboarding journeys, renewal metrics, or support analytics.
 </li>
 <li>
 Familiarity with AI/ML pipelines and experimentation frameworks that support data-driven innovation.
 
 
 </li>
 </ul>
 Perks!
 
 
 <ul>
 <li>
 You'll get to work on a category-leading product that customers love in a fun, high-growth industry! Check our Capterra and G2 reviews.
 </li>
 <li>
 4 ROLLER Recharge days per year (When we hit our goals each quarter, we take a well-earned day off together to relax, recharge, and celebrate our wins).
 </li>
 <li>
 Engage in our 'Vibe Tribe' - led by our team members; you can contribute to company-wide initiatives directly. Regular events and social activities, fundraising &amp; cause-related campaigns...you name it. We're willing to make it happen!
 </li>
 <li>
 Team Member Assistance Program to proactively support our team's health and wellbeing - access to coaching, education modules, weekly webinars, and more.
 </li>
 <li>
 16 weeks paid Parental Leave for primary carers and 4 weeks paid Parental Leave for secondary carers.
 </li>
 <li>
 Work with a driven, fun, and switched-on team that likes to raise the bar in all we do!
 </li>
 <li>
 Individual learning &amp; development budget plus genuine career growth opportunities as we continue to expand!
 
 
 </li>
 </ul>
 What You Can Expect
 
 
 <ul>
 <li>
 
 Initial call with our Talent Acquisition Manager
 
 You'll have an initial call with our Talent Acquisition Manager to chat through some of your experience to date, salary expectations and you can check off any initial questions you might have.
 </li>
 <li>
 
 Interview with the Hiring Manager
 
 You'll get to meet with the hiring manager to learn more about the role &amp; ROLLER whilst also talking through your experience in more detail.
 </li>
 <li>
 
 Loop Interviews
 
 This is where you will get to meet our wider ROLLER team to do a 'vibe check' on us to make sure our culture &amp; vibe meet what you are looking for!
 </li>
 <li>
 
 Offer
 
 If all lights are green and the fit feel right, we'll conduct reference checks and you'll receive an offer to join!
 </li>
 </ul>
</div>

Data Engineer

Ripple

<div><div>At Ripple, we're building a world where value moves like information does today. It's big, it's bold, and we're already doing it. Through our crypto solutions for financial institutions, businesses, governments and developers, we are improving the global financial system and creating greater economic fairness and opportunity for more people, in more places around the world. And we get to do the best work of our career and grow our skills surrounded by colleagues who have our backs.

If you're ready to see your impact and unlock incredible career growth opportunities, join us, and build real world value.</div>
At Ripple, we're building a world where value moves like information does today. It's big and bold, and we're already doing it. Through our crypto solutions for financial institutions, businesses, governments, and developers, we improve the global financial system. We craft greater economic fairness and opportunity for more people in more places globally. We perform the best work of our careers and develop our skills with colleagues who have our backs.

If you're ready to see your impact and embrace meaningful new challenges, join us, and build real world value.

The Work:

We're seeking a Senior Staff Engineer to act as the technical architect and strategic leader for Ripple's data platform. This role is one of the highest-impact individual contributor positions on the Data team. You will build a coherent, unified view of Ripple's data across all business units. You will establish the definitive source of truth for company metrics and lead our &quot;AI for Data&quot; transformation. You will collaborate across data teams and work directly with senior leadership in Data, Product, Engineering, and Go-to-Market to develop how Ripple understands itself through data. You won't just build systems; you will define the technical vision that connects them. This sits at the intersection of architecture, integration, governance, and applied AI.

What you'll do:
<ul>
<li>Build &quot;One View&quot; of Ripple by serving as the main architect for a Unified Data Fabric. Construct a well-rounded view of Ripple's data platforms, pipelines, and tools. Craft the systems and interoperability standards that bring data together across all business units for leadership, product, and GTM teams.</li>
<li>Compose and build the Ripple Metrics Store, a definitive, governed layer that serves as the single source of truth for business metrics across all business units.</li>
<li>Define metrics governance, ownership models, and validation frameworks. Build and maintain the Metrics Glossary in partnership with the Data Science team, and collaborators crafting a shared language for how Ripple measures its business.</li>
<li>Define and lead the AI roadmap for the Data organization setting the vision for how AI transforms the way Ripple builds, governs, and consumes data.</li>
<li>Enable conversational analytics and intelligence by architecting AI Agents that allow non-technical collaborators to self-serve insights directly from the data platform.</li>
<li>Automate data engineering workflows by encouraging use of AI-powered coding assistants for SQL/ETL generation. Define the standards, validation frameworks, and guidelines for AI-generated code across the team.</li>
<li>Lead cross-team build reviews, setting the technical bar for data architecture decisions across the organization.</li>
<li>Mentor and up-level engineers across data teams, raising the standard for system building, code quality, and engineering rigor.</li>
<li>Act as the main technical consultant to senior leadership across Data, Product, and Engineering regarding long-term technical bets, platform investments, and build-vs-buy decisions.</li>
</ul>
What you'll bring:
<ul>
<li>14+ years of experience in data engineering, data architecture, or related software engineering fields, with a significant portion spent in senior technical leadership or architect roles.</li>
<li>Having a track record of bringing together data ecosystems from multiple business units, you have built the connections that convert isolated data platforms into a consistent entity.</li>
<li>Deep expertise in modern data architecture, data mesh, lakehouse patterns, with hands-on experience in technologies like Spark, Kafka, Airflow, dBT, Databricks, and cloud-native data services (AWS, GCP, or Azure).</li>
<li>Experienced in metrics governance and semantic layers, you have established or planned metrics stores, business glossaries, or comparable systems that provide an organization's source of truth.</li>
<li>Demonstrated experience with AI/ML in data engineering contexts, whether building feature stores, deploying AI-powered data quality monitoring, integrating LLMs into developer workflows, or crafting agentic systems for data operations.</li>
<li>Architectural vision paired with execution ability, you can whiteboard a multi-year platform strategy and also get into the code to prototype critical path components.</li>
<li>With outstanding communication and influence skills, you comfortably present to VP/C-level audiences. You translate technical trade-offs into business language and build consensus among teams with competing priorities.</li>
<li>A collaborative, ego-free approach to leadership, you lead through influence and technical credibility, not through title.</li>
<li>Experience with blockchain data, on-chain analytics, or large-scale financial/payments data is a plus.</li>
<li>Direct involvement with LLM-enabled developer tools and agents, AI code synthesis, RAG-style data catalogs, natural language querying interfaces, or agent orchestration solutions is beneficial.</li>
<li>BS or equivalent experience in Computer Science or similar.</li>
</ul><div>
WHO WE ARE:

Do Your Best Work
<ul>
<li>The opportunity to build in a fast-paced start-up environment with experienced industry leaders</li>
<li>A learning environment where you can dive deep into the latest technologies and make an impact. A professional development budget to support other modes of learning.</li>
<li>Thrive in an environment where no matter what race, ethnicity, gender, origin, or culture they identify with, every employee is a respected, valued, and empowered part of the team.</li>
<li>In-office collaboration for moments that matter is important to our culture, and we give managers and teams the flexibility to decide which 10+ days a month they come in.</li>
<li>Bi-weekly all-company meeting - business updates and ask me anything style discussion with our Leadership Team</li>
<li>We come together for moments that matter which include team offsites, team bonding activities, happy hours and more!</li>
</ul>
Take Control of Your Finances
<ul>
<li>Competitive salary, bonuses, and equity</li>
<li>Competitive benefits that cover physical and mental healthcare, retirement, family forming, and family support</li>
<li>Employee giving match</li>
<li>Mobile phone stipend</li>
</ul>
Take Care of Yourself
<ul>
<li>R&amp;R days so you can rest and recharge</li>
<li>Generous wellness reimbursement and weekly onsite &amp; virtual programming</li>
<li>Generous vacation policy - work with your manager to take time off when you need it</li>
<li>Industry-leading parental leave policies. Family planning benefits.</li>
<li>Catered lunches, fully-stocked kitchens with premium snacks/beverages, and plenty of fun events</li>
</ul>
Benefits listed above are for full-time employees.

<div>Ripple is an Equal Opportunity Employer. We're committed to building a diverse and inclusive team. We do not discriminate against qualified employees or applicants because of race, color, religion, gender identity, sex, sexual identity, pregnancy, national origin, ancestry, citizenship, age, marital status, physical disability, mental disability, medical condition, military status, or any other characteristic protected by local law or ordinance.</div>
<div></div>
<div>Please find our UK/EU Applicant Privacy Notice and our California Applicant Privacy Notice for reference.</div></div></div>

Senior Staff Engineer — Data Engineering & Architecture

EARTH & ESTATES LLP

We&rsquo;re Hiring: Lead Data Engineer Location: California, USA (Bay Area &ndash; Local Candidates Only) Employment Type: W2 Only (All Visas Accepted Except H1) Experience: 6+ Years of Genuine Hands-on Experience RequiredWe are seeking an experienced, hands-on Senior Data Engineer to design, build, and scale modern data platforms supporting enterprise analytics, business intelligence, and healthcare data integrations. This role involves working with SQL Server, Azure, Databricks, Snowflake, and Python in real-world production environments, with a strong focus on cloud modernization and scalable data architecture.Key Responsibilities:-Design and maintain scalable ETL/ELT pipelines across cloud platformsLead migration of on-prem SQL Server workloads to Azure (ADF, Synapse, ADLS, Fabric)Architect and optimize data warehouses, data marts, and lakehouse architecturesWork with healthcare data systems (EHR, HL7, FHIR, HIPAA-compliant environments)Develop integrations using REST APIs, CDC, and event-driven architecturesImplement dimensional modeling and performance tuning strategiesBuild batch and streaming pipelines using Spark and KafkaCollaborate with BI, ML, and business stakeholdersEstablish monitoring, data quality checks, and CI/CD processesCore Skills:-Advanced SQL and performance tuningAzure (ADF, Synapse, Azure SQL, ADLS, Fabric)Databricks, Snowflake, BigQueryPython (PySpark), ScalaSpark (batch &amp; streaming), KafkaETL tools (ADF, SSIS, Airflow, dbt)BI tools (Power BI preferred)DevOps and data governance best practicesInterested candidates (local to Bay Area only, with 6+ years of genuine experience) may share their resume at:devang@acrtechnology.comJob Types: Full-time, ContractPay: $55.00 - $65.00 per hourWork Location: In person

Lead Data Engineer

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