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data infrastructure engineer

Ｃollective

<div>About Collective:
Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.
Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures (Ashton Kutcher and Guy Oseary), QED Investors, Google&rsquo;s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft.
About the role:
Most teams have the data they need but can&rsquo;t access it. This role is here to fix that.
We're hiring a senior engineer to build an internal data agent: a system that lets anyone at the company act as their own data analyst. Individuals can ask questions in plain English and get back correct, decision-ready answers or dashboards.
This is not a traditional data role. You'll operate across AI systems, data infrastructure, and product engineering. You'll be responsible both for building a powerful system and for ensuring the data it relies on is clean, consistent, and reliable.
The problem space is wide open. We&rsquo;re looking for a strategic operator to shape the technical direction, the data model, and system adoption.
What you'll do:<ul><li>
Develop agent infrastructure<ul><li>
Build retrieval, planning, and execution systems on top of real data</li><li>
Support multi-step reasoning and analysis workflows</li><li>
Integrate into internal tools</li></ul></li><li>
 Build an end-to-end analytics system<ul><li>
Create a natural language interface over our entire data stack</li><li>
Enable anyone to run complex analyses without writing SQL</li></ul></li><li>
Own and improve the data layer<ul><li>
Collaborate with product engineering to design and evolve clean, consistent data models</li><li>
Identify inconsistencies in the core schema and resolve them at the source</li></ul></li><li>
Build and maintain data pipelines<ul><li>
Own the reliability of our data infrastructure end-to-end</li><li>
Debug and fix broken systems (e.g. dbt models, pipeline failures)</li><li>
Make it easy to integrate new data sources into the data warehouse</li></ul></li><li>
Make it trustworthy<ul><li>
Ensure outputs are correct, consistent, and explainable</li><li>
Build evaluation loops, monitoring, and guardrails</li><li>
Eliminate ambiguity in metrics, definitions, and sources of truth</li><li>
Handle permissions, sensitive data, and edge cases</li></ul></li><li>
Drive adoption<ul><li>
Work directly with teams across EPD, Member Operations, Legal, and more</li><li>
Drive alignment on data definitions and system usage</li><li>
Turn this into the default way people interact with data</li></ul></li></ul>
What you'll bring:<ul><li>
 You are a product engineer working in data<ul><li>
You treat data models as part of the product, not a separate layer</li><li>
You have strong opinions on schema design, naming, and consistency</li><li>
You're comfortable identifying issues in production data and fixing them at the root</li></ul></li><li>
You are an owner, not a participant<ul><li>
You take vague, high-stakes problems and turn them into real systems</li><li>
You care about outcomes, not just implementation</li></ul></li><li>
You have strong data experience<ul><li>
Experience with data modeling, warehouses, and pipelines</li></ul></li><li>
You're an exceptional builder<ul><li>
You can go from idea architecture production</li><li>
You've built with LLMs, RAG, or agents in production</li><li>
You've shipped systems that people actually rely on</li></ul></li><li>
You have influence<ul><li>
You communicate effectively with both technical and non-technical stakeholders</li><li>
You can drive alignment across teams with competing priorities</li><li>
You're comfortable challenging existing systems and pushing for better approaches</li></ul></li></ul>
What we offer:<ul><li>
Hybrid Work Model: Based in San Francisco with a balance of in-office and remote flexibility.</li><li>
Fresh Lunch: Provided on in-office days.</li><li>
Commuter Support: $150 monthly reimbursement for transit expenses.</li><li>
Health &amp; Wellness: $200 quarterly reimbursement to support your well-being.</li><li>
Time Off: Flexible PTO plus 14 company holidays.</li><li>
Comprehensive Coverage: 100% medical, dental, and vision for employees; 75% coverage for dependents.</li><li>
Parental Leave: 16 weeks fully paid.</li><li>
Retirement &amp; Ownership: 401k plan plus an equity package.</li><li>
Team Connection: Quarterly virtual events and an annual in-person summit.</li></ul>
Compensation Range: $200K - $270K</div>

AI Data Engineer (Agent Platform)

Scale

Founding Data &amp; Operations EngineerSan Francisco, CA (On-Site) | $200K&ndash;$280K BaseBuild the Infrastructure Behind the Future of Global FinanceWe are building a next-generation financial platform that unifies banking, payments, and crypto into a single, seamless experience. Our mission is to expand financial access globally&mdash;particularly in regions where traditional systems have failed&mdash;and give millions of people a better way to move and manage money.Our team is intentionally small and senior. We&rsquo;ve previously built and scaled products used by hundreds of millions of users and generating billions in revenue. Now, we are doing it again&mdash;this time with immediate distribution through key partners and a clear path to global scale.We are looking for a Founding Data &amp; Operations Engineer to design and build the core systems that will power everything we do.What You&rsquo;ll Own<ul><li>Architect and build the data infrastructure that underpins our entire platform</li><li>Create systems that enable accurate financial ledgers across multiple partners and accounts</li><li>Design pipelines that support fraud detection, AML workflows, and risk modeling</li><li>Build a unified analytics layer that gives teams real-time, reliable insights</li><li>Establish secure data access patterns that maintain governance, lineage, and compliance</li><li>Define and document best practices for infrastructure and data systems as we scale</li></ul>What You Bring<ul><li>5+ years of experience building and shipping data platforms or pipelines at scale</li><li>Deep expertise with Terraform, dbt, SQL, and AWS</li><li>Strong experience in FinTech environments (banking, payments, crypto, lending, etc.)</li><li>Background in data modeling, ETL/ELT, or event-driven systems</li><li>Ability to think across systems&mdash;data, backend, and infrastructure</li><li>Clear and effective technical communication</li></ul>What Makes You Stand Out<ul><li>Experience with global payments, ledgering, or financial systems</li><li>Exposure to fraud detection or compliance workflows</li><li>Ability to translate complex data into clear insights and systems</li><li>Experience working in small, high-performance teams</li></ul>Why This Role Is Different<ul><li>Founding-level ownership: You will define core architecture and systems from the ground up</li><li>Immediate impact: Your work directly powers products used by millions</li><li>High-caliber team: Work alongside experienced operators and engineers with proven track records</li><li>Speed and autonomy: No layers, no bureaucracy&mdash;just execution</li><li>Global scale: Build infrastructure that supports a worldwide user base from day one</li></ul>Our CultureWe operate with a strong bias toward ownership, speed, and precision. Every person on the team contributes meaningfully to both product and company direction. We value individuals who take initiative, communicate openly, and are driven to build at a high level.Compensation<ul><li>Base salary: $200,000&ndash;$280,000</li><li>Additional compensation and benefits discussed during the process</li></ul>Final ThoughtThis is an opportunity to build the data foundation of a global financial platform from the earliest stages. If you are motivated by ownership, technical depth, and real-world impact, we want to hear from you.Pay: $200,000.00 - $280,000.00 per yearApplication Question(s):<ul><li>Do you have experience working at banking/credit card/crypto/remittances/lending startups?</li><li>Do you have experience with data modeling, ETL/ELT, or event-driven systems?</li><li>Do you have extensive hands-on experience building scalable data architectures in a consumer-oriented FinTech environment using Terraform, dbt, and SQL?</li><li>Do you have at least 5+ years building and shipping data pipelines and platforms?</li><li>Do you have experience generally across the backend: working with Postgres, Redis, AWS, etc?</li></ul>Work Location: In person

Senior Data Engineer

Discord

Discord is used by over 200 million people every month for many different reasons, but there&rsquo;s one thing that nearly everyone does on our platform: play video games. Over 90% of our users play games, spending a combined 1.5 billion hours playing thousands of unique titles on Discord each month. Discord plays a uniquely important role in the future of gaming. We are focused on making it easier and more fun for people to talk and hang out before, during, and after playing games.We're looking for someone who gets excited about building data infrastructure at massive scale and cares deeply about the gaming communities we serve. Someone with passion for building lovable products for Discord users and Discord engineers. We're building the next generation Data Platform that powers decisions for one of the most vibrant platforms in the world. If you're the kind of Staff Engineer who sees ambiguity as an invitation &mdash; who builds systems that make whole teams faster, shapes technical strategy across the org, and wants your decisions to directly impact millions of gamers worldwide &mdash; we want to talk to you. To learn more about Discord's Data Platform, read our engineering blog, including how we built our modern data stack leveraging open-source tools! This position is based in our San Francisco office. What You'll Be Doing Own the technical direction of major Data Platform initiatives like GRC, scaling, or stream processing, from problem to production system and post-launch health Be a force multiplier: build reusable primitives, unblock teammates, and raise the quality bar across the team Stay a top code contributor. You write real production code while helping others reach the same bar Partner with XFN stakeholders to translate business problems into clear technical strategy Champion debate, decide, and commit and 80/20 thinking to drive robust technical solutions supporting multiple team What you should have 7+ years of software engineering experience with a track record of driving large, ambiguous technical initiatives end-to-end Expertise in distributed systems and data infrastructure at scale. You've anticipated hard problems before they became incidents Demonstrated ability to multiply a team's impact through architectural thought leadership, design reviews, reusable abstractions, and well-timed mentorship Strong technical judgment: when to go fast vs. slow, when to build vs. integrate, and how to bring stakeholders along Cross-functional influence: you've driven alignment across engineering, product, and business without relying on authority Bonus Points Passion for Discord and gaming Experience with data governance, privacy compliance, real-time analytics infrastructure, or cost optimization in large-scale data environments Candidates must reside in or be willing to relocate to the San Francisco Bay Area (Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties). Relocation assistance may be available. The US base salary range for this full-time position is $248,000 to $279,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.Why Discord?Discord plays a uniquely important role in the future of gaming. We're a multiplatform, multigenerational and multiplayer platform that helps people deepen their friendships around games and shared interests. We believe games give us a way to have fun with our favorite people, whether listening to music together or grinding in competitive matches for diamond rank. Join us in our mission! Your future is just a click away! Discord is committed to inclusion and providing reasonable accommodations during the interview process. We want you to feel set up for success, so if you are in need of reasonable accommodations, please let your recruiter know. Please see our Applicant and Candidate Privacy Policy for details regarding Discord&rsquo;s collection and usage of personal information relating to the application and recruitment process by clickingHERE.

Staff Software Engineer, Data Platform

OpenAI

<div>
 
 About The Team
 
 
 
 The Applied team works across research, engineering, product, and design to bring OpenAI&rsquo;s technology to consumers and businesses.
 
 
 We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.
 
 
 
 About The Role
 
 
 
 We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI!
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse.
 </li>
 <li>
 Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
 </li>
 <li>
 Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions.
 </li>
 <li>
 Implement robust and fault-tolerant systems for data ingestion and processing.
 </li>
 <li>
 Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.
 </li>
 <li>
 Ensure the security, integrity, and compliance of data according to industry and company standards.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering).
 </li>
 <li>
 Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
 </li>
 <li>
 Experience with distributed processing technologies and frameworks, such as Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).
 </li>
 <li>
 Expertise with any of ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.
 </li>
 <li>
 Solid understanding of Spark and ability to write, debug and optimize Spark code.
 
 
 </li>
 </ul>
 This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees.
 
 
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
 
 Compensation Range: $230K - $385K
</div>

Data Engineer, Analytics

Figma

<div>
 Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma&rsquo;s platform helps teams bring ideas to life&mdash;whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
 
 
 We are looking for an experienced Data Engineer to partner with our Data Science and Data Infrastructure teams to own and scale our data pipelines. You&rsquo;ll also work closely with stakeholders across business teams including sales, marketing, and finance to ensure that the data they need arrives promptly and reliably. You&rsquo;ll play an integral role in building the metrics and self-serve reporting capabilities to unlock Figma&rsquo;s next phase of growth.
 
 
 This is a great role for an individual who is passionate about working with data and data systems, and who loves solving problems. You&rsquo;ll have a good sense for when it makes sense to build fast, scrappy solutions to unblock a key stakeholder vs. when to push back or bring in an outside service. The ideal candidate will be a great communicator who can help coordinate across multiple internal and external teams and takes pride in building end-to-end projects.
 
 
 This is a full time role that can be held from one of our US hubs or remotely in the United States.
 
 
 
 What you'll do at Figma
 
 
 :
 
 
 
 <ul>
 <li>
 Own, build, and maintain scalable data pipelines that connect various cloud data sources.
 </li>
 <li>
 Develop a deep understanding of Figma&rsquo;s core data models and optimize data pipelines for scale.
 </li>
 <li>
 Partner with the Data Science and Data Infrastructure teams to build new foundational data sets that are trusted, well understood, and enable self-service.
 </li>
 <li>
 Work with a wide range of cross-functional stakeholders to derive requirements and architect shared datasets; ability to document, simplify and explain complex problems to different types of audiences.
 </li>
 <li>
 Establish best practices for the development of specialized data sets for analytics and modeling.
 
 
 </li>
 </ul>
 We'd love to hear from you if you have:
 
 
 <ul>
 <li>
 4+ years in a relevant field.
 </li>
 <li>
 Fluency with both SQL and Python.
 </li>
 <li>
 Familiarity with Snowflake, dbt, Dagster, and ETL/reverse ETL tools.
 </li>
 <li>
 Excellent judgment and creative problem solving skills.
 </li>
 <li>
 A self-starting mindset along with strong communication and collaboration skills.
 
 
 </li>
 </ul>
 While not required, it&rsquo;s an added plus if you also have:
 
 
 <ul>
 <li>
 Knowledge in data modeling methodologies to design and build robust data architectures for insightful analytics.
 </li>
 <li>
 Experience with business systems such as Salesforce, Customer IO, Stripe, NetSuite is a big plus.
 
 
 </li>
 </ul>
 At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you&rsquo;re excited about this role but your past experience doesn&rsquo;t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
 
 
 
 Pay Transparency Disclosure
 
 
 
 If based in Figma&rsquo;s San Francisco or New York hub offices, this role has the annual base salary range stated below.
 
 
 Job level and actual compensation will be decided based on factors including, but not limited to, individual qualifications objectively assessed during the interview process (including skills and prior relevant experience, potential impact, and scope of role), market demands, and specific work location. The listed range is a guideline, and the range for this role may be modified. For roles that are available to be filled remotely, the pay range is localized according to employee work location by a factor of between 80% and 100% of range. Please discuss your specific work location with your recruiter for more information.
 
 
 Figma offers equity to employees, as well a competitive package of additional benefits, including health, dental &amp; vision, retirement with company contribution, parental leave &amp; reproductive or family planning support, mental health &amp; wellness benefits, generous PTO, company recharge days, a learning &amp; development stipend, a work from home stipend, and cell phone reimbursement. Figma also offers sales incentive pay for most sales roles and an annual bonus plan for eligible non-sales roles. Figma&rsquo;s compensation and benefits are subject to change and may be modified in the future.
 
 
 Annual Base Salary Range:
 
 
 $140,000&mdash;$348,000 USD
 
 
 At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status
 
 ,
 
 or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
 
 
 We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com. These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities.
 
 
 Examples of accommodations include but are not limited to:
 
 
 <ul>
 <li>
 Holding interviews in an accessible location
 </li>
 <li>
 Enabling closed captioning on video conferencing
 </li>
 <li>
 Ensuring all written communication be compatible with screen readers
 </li>
 <li>
 Changing the mode or format of interviews
 
 
 </li>
 </ul>
 To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding.
 
 
 By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice.
</div>

Data Engineer

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.<h1 class="jobSectionHeader">
The Opportunity</h1>
We are building something unprecedented &mdash; an AI foundation that will push the frontier on what is possible today across drug discovery research, from target identification and disease biology through translational science.
The Applied Intelligence for Discovery (AI4D) team is a newly formed group within Lilly Research Laboratories that operates at the intersection of scientific delivery and core platform development. AI4D&rsquo;s mission is connecting scientists to petabyte-scale data through natural language interfaces, automated analysis workflows, and intelligent search &mdash; and to convert early deployments into repeatable system standards and evaluation practices that scale across therapeutic areas.
As a Scientific Data Engineer, you will close that gap. You will build the semantic layer, data harmonization infrastructure, AI-ready data products, and lakehouse architecture that bridge how data is stored and how AI systems need to consume it. You will be working at the intersection of the data infrastructure team and the generative AI engineers who build the systems scientists interact with.<h1 class="jobSectionHeader">
Responsibilities</h1><h2 class="jobSectionHeader">
Data Harmonization and Lakehouse Architecture</h2><ul><li>
Design and build the data architecture that transforms raw and processed omics data into harmonized, AI-consumable layers</li><li>
Build and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI system consumption</li><li>
Implement data quality monitoring, automated profiling, and validation checks across harmonization layers</li><li>
Create versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environment</li><li>
Partner with the teams to extend harmonization patterns as data modalities expand beyond genomics and proteomics into spatial transcriptomics, perturbational data (Perturb-Seq), single-cell, and digital pathology</li></ul><h2 class="jobSectionHeader">
Semantic Layer and Schema Engineering</h2><ul><li>
Design and maintain a semantic layer over Lilly&rsquo;s multi-omics databases that enables AI systems</li><li>
Create comprehensive schema documentation: table descriptions, column-level annotations, relationship mappings, business logic rules, and domain-specific constraints (e.g., statistical thresholds, unit conventions, experimental design metadata)</li><li>
Develop gold-standard question/SQL pairs for each major database, in collaboration with computational biologists and Generative AI Engineers, to serve as training data, few-shot examples, and evaluation benchmarks</li><li>
Build and maintain a data dictionary and ontology mapping layer that translates how scientists think and speak about data (gene names, pathway terms, assay types) into how the data is physically stored</li></ul><h2 class="jobSectionHeader">
AI-Ready Data Products</h2><ul><li>
Build and manage vector embedding pipelines for scientific documents, study metadata, and structured data descriptions to power RAG-based retrieval</li><li>
Build integration pipelines that connect heterogeneous data sources &mdash; omics databases, internal publications, electronic lab notebooks, assay results, and clinical annotations &mdash; into a unified, queryable layer</li><li>
Develop and enforce metadata standards that ensure new data sources are AI-accessible from the point of ingestion, not retroactively</li><li>
Design data products that serve multiple consumption patterns: direct SQL access for computational biologists, structured feeds for ML training pipelines, and semantic interfaces for LLM-powered tools</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
Bachelors degree in Computer Science, Data Engineering, Bioinformatics, or a related field + 8 years data engineering experience OR Masters degree and 5 years data engineering experience</li><li>
Demonstrated expertise in building data pipelines, ETL/ELT workflows, and data products that serve downstream AI/ML systems</li></ul><h1 class="jobSectionHeader">
Additional Skills/Preferences</h1><ul><li>
Phd in data or related field</li><li>
Strong SQL skills and experience with complex relational database schemas (hundreds of tables, multi-level joins, domain-specific conventions)</li><li>
Experience with modern data platform technologies, including at least one of: Databricks, Snowflake, or equivalent lakehouse platforms</li><li>
Experience with modern data engineering tools: dbt, Spark, Airflow, or similar orchestration and transformation frameworks</li><li>
Proficiency in Python for data processing, scripting, and pipeline development</li><li>
Experience with cloud data platforms (AWS preferred: Redshift, Athena, Glue, S3, or similar)</li><li>
Familiarity with at least one of: vector databases, embedding pipelines, or semantic layer tooling</li><li>
Strong communication skills &mdash; you can work effectively with both engineers who think in schemas and scientists who think in biology</li><li>
Experience with biomedical or scientific data: omics datasets (RNA-seq, proteomics, GWAS), clinical data, or laboratory information management systems</li><li>
Experience in pharmaceutical, biotech, or life sciences environments</li></ul><ul><li>
Familiarity with biomedical ontologies and controlled vocabularies (Gene Ontology, MeSH, ChEBI, HGNC) and their application to data integration</li><li>
Experience building data products that serve AI/ML systems &mdash; feature stores, training datasets, evaluation benchmarks, or semantic annotations for text-to-SQL</li><li>
Knowledge of data governance practices in regulated industries: data lineage, access controls, versioning, and auditability</li><li>
Experience with knowledge graph technologies (Neo4j, Amazon Neptune, RDF/SPARQL) or graph-based data modeling</li><li>
Deep experience with Databricks ecosystem: Unity Catalog for data governance, Delta Lake for ACID transactions, MLflow integration, and Databricks SQL for analytics workloads</li><li>
Experience designing data architectures that bridge traditional bioinformatics workflows (Nextflow, R/Bioconductor) with modern lakehouse consumption patterns</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
$166,500 - $266,200
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 - Scientific Data Engineer

About the Team
 
OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners.
 
As a Data Center Infrastructure Mechanical Engineer, you will help design, validate, and scale the cooling and mechanical systems that make high-density AI compute possible. You will work across thermal architecture, equipment development, manufacturing validation, construction, commissioning, deployment, and operations, partnering with research, hardware engineering, data center engineering, supply chain, EHS, operations, and external delivery partners.
 
About The Role
 
We are seeking a senior mechanical infrastructure engineer to lead the development of reliable, efficient, safe, and scalable thermal architectures for high-density, liquid-cooled AI data centers. This role is ideal for someone who can translate evolving compute and rack-level thermal requirements into practical infrastructure designs, evaluate complex equipment and vendor solutions, and drive technical decisions across facilities, hardware, controls, telemetry, testing, commissioning, and operations.
 
The ideal candidate has deep hands-on experience with mission-critical mechanical systems at data center or comparable critical infrastructure scale, including chilled water plants, condenser water systems, cooling towers, dry coolers, pumps, heat exchangers, CDUs, manifolds, CRAHs, air handlers, filtration, water treatment, controls, liquid distribution, and high-density rack cooling interfaces.
 
Key Responsibilities
 
Define mechanical and cooling infrastructure requirements and reference architectures for AI data center campuses, including heat rejection, chilled water, condenser water, liquid cooling distribution, air handling, containment, filtration, water treatment, controls, and metering.
 
Review and develop basis-of-design documents, design narratives, P&IDs, mechanical schedules, equipment specifications, thermal capacity models, hydraulic models, CFD analysis, controls sequences, and commissioning requirements.
 
Evaluate mechanical architectures for high-density compute, including direct-to-chip liquid cooling, CDU topology, facility water interfaces, manifolds, quick disconnects, hoses, heat exchangers, pumping strategies, leak detection, serviceability, and failure isolation.
 
Partner with electrical, controls, hardware, networking, construction, and operations teams to ensure cooling systems support liquid-cooled GPU rack deployments and reliable facility operation.
 
Develop technical specifications and acceptance criteria for chillers, cooling towers, dry coolers, evaporative coolers, pumps, heat exchangers, CDUs, manifolds, valves, filters, water treatment systems, CRAHs, air handlers, VFDs, controls panels, sensors, and monitoring devices.
 
Lead technical evaluation of equipment vendors, manufacturers, design consultants, commissioning agents, contractors, and testing laboratories; review submittals, P&IDs, control diagrams, performance curves, test reports, certifications, and quality documentation.
 
Drive factory acceptance testing, site acceptance testing, witness testing, pressure testing, leak testing, thermal performance testing, reliability testing, interoperability testing, and integrated systems testing for critical equipment and high-density rack deployments.
 
Help design and operate a hardware and data center infrastructure R&D laboratory used to validate new cooling equipment, liquid-cooled GPU rack designs, operating envelopes, fault scenarios, telemetry, and facility-hardware interactions.
 
Collaborate with hardware manufacturers to evaluate L10 and L11 test procedures, yield, throughput, reliability, serviceability, and readiness for large-scale deployment.
 
Define telemetry and controls requirements for mechanical and supporting electrical systems, including temperatures, flow rates, differential pressure, pump status, valve position, chiller status, CDU status, coolant quality, leak detection, alarms, control states, and rack-level thermal signals.
 
Analyze lab data, operational incidents, thermal excursions, flow excursions, pressure excursions, leak events, contamination events, nuisance alarms, controls alarms, and rack-level thermal failures to improve designs, procedures, vendor quality, and reliability models.
 
Create clear engineering documentation, standards, test procedures, commissioning scripts, operating procedures, decision records, risk registers, and executive-ready technical summaries.
 
Provide senior technical escalation support during design reviews, construction, manufacturing validation, commissioning, startup, production deployment, vendor testing, and operational events.
 
Mentor partner teams and raise the technical bar for mechanical design, thermal validation, safety, water quality, documentation, reliability, and operational rigor.
 
Required Qualifications
 
Extensive senior-level experience in data center mechanical engineering, mission-critical facilities, high-performance computing infrastructure, thermal systems, or comparable critical infrastructure environments, typically gained through 10+ years of relevant work or equivalent depth of experience.
 
Deep expertise in mechanical design, commissioning, operations, maintenance, reliability, and lifecycle management at large campus or multi-site scale.
 
Hands-on experience with chilled water systems, condenser water systems, process cooling water, cooling towers, dry coolers, evaporative cooling, pumps, heat exchangers, CDUs, manifolds, CRAHs, air handlers, filtration, water treatment, valves, piping, controls, and monitoring systems.
 
Experience designing, testing, certifying, commissioning, or operating equipment used in high-density compute or mission-critical environments, including liquid cooling systems, CDUs, high-flow hydronic systems, heat exchangers, rack manifolds, quick disconnects, and thermal monitoring systems.
 
Experience reviewing and producing technical design packages, equipment specifications, design narratives, sequence-of-operations, CFD or hydraulic studies, test plans, commissioning scripts, operating procedures, and acceptance criteria.
 
Proven ability to evaluate and manage external engineering firms, equipment manufacturers, construction partners, commissioning providers, testing laboratories, and strategic suppliers.
 
Strong understanding of product safety, agency certification, mechanical code compliance, pressure safety, environmental requirements, AHJ coordination, utility requirements, water quality programs, and standards relevant to critical mechanical infrastructure.
 
Experience with factory acceptance testing, site acceptance testing, integrated systems testing, leak testing, pressure testing, thermal performance testing, failure-mode testing, root-cause analysis, and corrective-action management.
 
Ability to use data, models, field observations, and engineering judgment to make decisions under ambiguity and communicate risk clearly to technical and non-technical stakeholders.
 
Bachelor's degree in Mechanical Engineering, Electrical Engineering, Systems Engineering, or a related technical field, or equivalent practical experience.
 
Preferred Qualifications
 
Advanced degree in mechanical engineering, thermal sciences, fluid mechanics, systems engineering, or a related discipline.
 
Professional Engineer license, Chartered Engineer status, or comparable professional certification.
 
Direct experience with AI infrastructure, hyperscale data centers, HPC clusters, GPU rack deployments, direct-to-chip liquid cooling, immersion cooling, or high-density rack thermal design.
 
Experience with high-density liquid cooling architectures, CDU qualification, facility water interface specifications, coolant chemistry, leak detection, quick disconnects, rack manifolds, cold plates, and thermal controls for accelerated compute.
 
Experience qualifying new mechanical or thermal products from concept through prototype, certification, manufacturing ramp, field deployment, and lifecycle support.
 
Experience evaluating L10 and L11 manufacturing test validation procedures, yield, throughput, burn-in, reliability screens, and test coverage for liquid-cooled GPU racks or similar complex systems.
 
Experience with BMS, EPMS, DCIM, SCADA, PLCs, chiller controls, pump controls, CDU controls, data historians, digital twins, CFD model validation, and reliability analytics.
 
Experience managing global, multi-site equipment manufacturing programs or data center programs across matrixed organizations and partner ecosystems.
 
Familiarity with sustainability, energy efficiency, PUE, WUE, CUE, water stewardship, grid constraints, demand response, renewable energy integration, heat reuse, and low-carbon infrastructure design considerations.
 
Work Environment and Travel
 
This role may require periodic travel to data center campuses, manufacturing partners, equipment suppliers, laboratories, construction sites, and commissioning activities.
 
The engineer should be comfortable working in office, lab, manufacturing, construction, and operating data center environments, including environments that require PPE, safety briefings, lockout/tagout discipline, water or chemical handling discipline, and coordination with site operations.
 
Work may include time-sensitive technical escalations during commissioning, startup, production deployment, vendor testing, leak events, thermal events, water treatment events, or operational incidents.
 
About OpenAI
 
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
For additional information, please see
 
OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement
 
.
 
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through
 
this form
 
. No response will be provided to inquiries unrelated to job posting compliance.
 
We are committed to providing reasonable accommodations to applicants with disabilities.
 
OpenAI Global Applicant Privacy Policy
 
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
Compensation
 
$257K – $327K + Offers Equity

Data Center Infrastructure Mechanical Engineer

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