data architect

Work From Home

<div><h5 class="jobSectionHeader">This is OUR story... and YOUR next chapter</h5>
At HCA Healthcare, our Digital Transformation and Innovation (DT&amp;I) team is redefining what&rsquo;s possible inpatient care. Byleveragingthe power of artificial intelligence, automation, and digital technologies, DT&amp;I is helping drive meaningful improvements in clinical outcomes, reduce manual workload, and expand the reach of our care teams. Ifyou'repassionate about using technology to improve human life, this is where your work truly matters<h5 class="jobSectionHeader">
What you will accomplish in this role</h5> 
What you will do:
Core Competencies
The following are highlighted entrepreneurial competencies and core expectations for the job/role:<ul><li>
Strategic thinking and architectural leadership</li><li>
Deep technical expertise in cloud data platforms</li><li>
Strong problem-solving and systems design skills</li><li>
Ability to bridge business, clinical, and technical domains</li><li>
Clear written and verbal communication</li></ul>
This role will focus on setting technical direction on groups of applications and similar technologies as well as taking responsibility for the implementation of technically robust solutions encompassing all business, architecture, and technology constraints.
Technical Leadership &amp; Architecture<ul><li>
Define and own enterprise-scale data architecture patterns for multi-modal ingestion and Lakehouse platforms on Google Cloud Platform.</li><li>
Architect and evolve document-centric and unstructured data pipelines that support ingestion, enrichment, embedding, indexing, storage, and retrieval at scale.</li><li>
Lead the design of intelligent ingestion frameworks leveraging LLMs and advanced techniques (e.g., semantic chunking, embeddings, metadata extraction, classification, and enrichment).</li><li>
Establish architectural standards for cost-optimized, high-throughput ingestion across batch, streaming, and event-driven workloads.</li><li>
Drive platform designs that support search, analytics, and downstream AI/ML use cases in partnership with the AI/ML organization.</li></ul>
Lakehouse &amp; Data Platform Design<ul><li>
Architect and manage enterprise Lakehouse environments using technologies such as BigQuery, Apache Iceberg, Delta Lake, and GCS.</li><li>
Ensure strong design around schema evolution, ACID compliance, partitioning strategies, metadata management, and lifecycle policies.</li><li>
Optimize storage and compute usage to balance performance and cost across large-scale document and data repositories.</li><li>
Design data models and access patterns that support both analytical and AI-driven workloads.</li></ul>
Ingestion, Processing &amp; AI Enablement<ul><li>
Design and oversee ETL/ELT and ingestion pipelines using Dataflow, Dataproc, Pub/Sub, Cloud Run, GKE, and related services.</li><li>
Integrate AI/ML services into ingestion and processing pipelines for document understanding and content intelligence in partnership with that practice area.</li><li>
Partner with AI/ML teams to enable embedding generation, vector storage, and retrieval patterns aligned with enterprise governance standards.</li><li>
Ensure ingestion frameworks are resilient, observable, and designed for continuous evolution.</li></ul>
API Architecture &amp; Governance 
<ul><li>
Design and implement enterprise-grade REST and event-driven APIs aligned with OpenAPI specifications, versioning standards, and backward compatibility principles.</li><li>
Define and enforce API governance frameworks including naming conventions, authentication patterns, rate limiting, pagination strategies, and error handling standards.</li><li>
Architect API layers that serve both human-facing applications and AI agent consumers, ensuring consistent contract design across all downstream integrations.</li><li>
Collaborate with platform and engineering teams to establish API lifecycle management practices including deprecation policies, schema validation, and automated compliance checks.</li><li>
Design secure API access patterns for PHI-sensitive and regulated data, incorporating encryption, scoping, and audit logging requirements.</li><li>
Partner with vendor and internal delivery teams to review, validate, and approve API designs prior to implementation, ensuring alignment with enterprise architecture standards.</li></ul>
Governance, Security &amp; Compliance<ul><li>
Define and enforce best practices for data governance, security, privacy, and compliance (HIPAA, GDPR) across structured and unstructured data.</li><li>
Ensure architectural alignment with enterprise policies for data retention, lineage, access control, and auditability.</li><li>
Participate in and lead architectural design reviews to ensure adherence to standards and patterns.</li></ul>
Collaboration &amp; Influence<ul><li>
Collaborate with business, clinical, analytics, and engineering stakeholders to translate requirements into scalable architectural solutions.</li><li>
Provide architectural guidance for cloud migrations and modernization initiatives involving document and data platforms.</li><li>
Maintain a holistic view of enterprise information assets through diagrams, reference architectures, and technical roadmaps.</li><li>
Act as a technical mentor and advisor to senior engineers and architects.</li></ul><h6 class="jobSectionHeader">
What qualifications you will need:</h6><ul><li>
Bachelor's degree in computer science, related technical field, or equivalent experience required</li><li>
Master's degree in computer science or related field preferred</li><li>
3+ years of experience in Cloud Data or Information Architect required</li><li>
5+ years of experience in Healthcare preferred</li><li>
10+ years of experience in Information Technology required</li></ul>
A successful candidate will demonstrate:<ul><li>
Deep experience designing enterprise data architectures on Google Cloud Platform or other Cloud Service Providers.</li><li>
Hands-on expertise with GCP services, including:</li><li>
BigQuery, Cloud Storage, Dataflow, Dataproc</li><li>
Pub/Sub, Cloud Run, GKE, Cloud Functions</li><li>
Bigtable, Cloud SQL, Cloud Spanner</li><li>
Strong knowledge of Lakehouse technologies and formats: Iceberg, Delta Lake, Parquet, Avro, JSON.</li><li>
Experience with document and unstructured data processing, including ingestion, enrichment, and indexing.</li><li>
Practical experience integrating LLMs and AI frameworks (e.g., Vertex AI, LangChain, embeddings, RAG patterns) into data pipelines.</li><li>
Proficiency in Python, SQL, and JVM-based languages (Java/Scala).</li><li>
Experience with CI/CD, DevOps, and infrastructure-as-code for data platforms.</li><li>
Strong understanding of data security, privacy, and regulatory requirements in cloud environments.</li><li>
Ability to analyze complex problems, modernize legacy pipelines, and design scalable solutions.</li><li>
Ability to communicate complex architectures clearly to both technical and non-technical audiences.</li></ul>
Certifications (a plus, but not required):<ul><li>
GCP Professional Data Engineer</li><li>
GCP Professional Cloud Architect</li></ul>
PHYSICAL DEMANDS/WORKING CONDITIONS (Specific statements of physical effort required and description of work environment; e.g., prolonged sitting at CRT. required travel %)
Prolonged sitting or standing at computer workstation including use of mouse, keyboard, and monitor.
Requires ability to provide after-hours support.
At HCA Healthcare, we are committed to fostering a culture of growth that allows you to build the career of a lifetime. We encourage you to apply for our Principal Data Architect today. We review all applications promptly, and qualified candidates will be contacted to continue the process. Join us!
We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.</div>

Principal Data Architect

Imagineeer

<div><div><div>Benefits:</div>
<ul><li>401(k) matching</li>
<li>Competitive salary</li>
<li>Health insurance</li>
<li>Paid time off</li>
</ul></div><div><div>About this Role: 
</div>
<div> 
The Data Architect / Enterprise Data Analyst will provide data strategy, architecture, and analytics expertise to support enterprise data initiatives across the U.S. Department of Health and Human Services (HHS). This role will define and implement data architecture frameworks, data governance standards, and enterprise data management (EDM) solutions to improve data quality, accessibility, security, and interoperability across systems and organizations. 
</div>
<div> 
The ideal candidate will have experience working in federal data environments, including designing enterprise data models, developing data integration strategies, and supporting data modernization and cloud migration projects. The role also requires strong collaboration skills to work with IT leadership, system owners, data stewards, and mission stakeholders to enable informed decision-making through trusted and well-governed data. 
</div><div>Key Responsibilities: 
</div><ul><li>Develop logical data models aligned to HRIT product lines, ensuring full compliance with HHS data governance policies to support the modernization of Human Capital Management (HCM) capabilities.</li></ul> 
<ul><li>Develop a comprehensive Data Migration Plan, including a phased migration strategy, data transformation protocols, validation and testing procedures, and rollback contingencies to support the transition to the Target State of HRIT modules.</li></ul> 
<ul><li>Support the design, development, testing, and deployment of HRIT applications and APIs, ensuring seamless data integration across a consolidated and modernized HCM platform.</li></ul> 
<ul><li>Deliver a comprehensive data integrity approach, ensuring robust data quality checks are in place to support the unified platform.</li></ul> 
<ul><li>Collaborate with the Data Governance Architect to establish a robust Data Stewardship framework.</li></ul> 
<ul><li>Support the technical team in developing and testing integrations between enterprise systems, leveraging technologies such as Web Services, REST/SOAP APIs, and</li></ul> 
<div>Integration Broker. Perform rigorous testing to ensure accurate and reliable data transmission across interconnected applications. 
</div><ul><li>Develop reports, queries, and analytics solutions to support business intelligence and operational insights.</li></ul> 
<ul><li>Create and maintain technical documentation for all configurations, customizations, and integrations.</li></ul> 
<ul><li>Collaborate with functional analysts, DBAs, and infrastructure teams to optimize system performance and reliability.</li></ul> 
<ul><li>Support upgrades, patches, and maintenance activities with minimal operational disruption.</li></ul> 
<ul><li>Apply federal compliance best practices, including security (NIST), accessibility (Section 508), and records management.</li></ul> 
<ul><li>Provide mentorship to junior developers and contribute to team knowledge through code reviews and technical guidance.</li></ul><div> 
 
</div><div>Qualifications and Skills: 
</div><ul><li>Bachelor&rsquo;s degree in Computer Science, Information Technology, or a related discipline.</li></ul> 
<ul><li>Proficient in SQL and relational database design, supporting scalable and efficient data solutions.</li></ul> 
<ul><li>Proven success working within federal government systems or comparable enterprise environments.</li></ul> 
<ul><li>At least 10 years of experience working as a Data Analyst, Data Modelling and/or Business Intelligence Domain.</li></ul><div> 
</div>
<ul><li>Eligible to obtain and maintain a Public Trust clearance/must be a US Citizen</li></ul> 
<ul><li>Certified in data governance and management (e.g., CDMP, DGCP).</li></ul> 
<ul><li>Hands-on experience implementing the Federal Data Strategy and supporting open data initiatives.</li></ul> 
<ul><li>In-depth knowledge of the Federal Enterprise Architecture Framework, including HHS EA (HHS-OCIO-OES-2024-10-005).</li></ul> 
<ul><li>Skilled in conducting data privacy impact assessments and applying NIST data security guidelines.</li></ul> 
<ul><li>Familiar with AI governance, and responsible machine learning practices.</li></ul> 
<ul><li>Proficient in cloud-based data governance, master data management, and data architecture principles.</li></ul> 
<ul><li>Experienced with business intelligence and data visualization tools.</li></ul> 
<ul><li>Knowledgeable in records management standards and federal compliance procedures.</li></ul> 
<div>Desired Skills and Competencies: 
</div><ul><li>Experience supporting HHS or other federal health agencies (CMS, NIH, HRSA, FDA, CDC).</li>
<li>Familiarity with federal data policies such as the Federal Data Strategy and CDO requirements.</li>
<li>Experience with enterprise data warehouses or data lakes.</li>
<li>Certifications such as CDMP, AWS Data Analytics, Azure Data Engineer, or DAMA.</li>
<li>Knowledge of FHIR, HL7, NIEM or federal data interoperability standards.</li>
<li>Experience with API integrations, service-oriented architecture (SOA), or microservices.</li>
</ul>
</div>Flexible work from home options available.</div>

Data Architect-Enterprise Data Analyst

CodeNinja

<div>About CodeNinja
CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
Role Purpose
Lead the ERP program&rsquo;s data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
Key Responsibilities<ul><li>Conduct comprehensive assessment of legacy data sources:</li></ul>
o Inventory, Maintenance (MRO), Procurement, HR, Technical Docs<ul><li>Identify:</li></ul>
o Data quality issues (duplicates, missing, inconsistencies)
o Data ownership and governance gaps
o Redundant/siloed datasets<ul><li>Define data cleansing and standardization approach</li><li>Produce Data Readiness Assessment Report</li><li>Define end-to-end Data Migration Strategy, including:</li></ul>
o Migration approach (phased, module-wise, or big-bang)
o Data prioritization (master data vs transactional vs historical)<ul><li>Develop Data Mapping Specifications:</li></ul>
o Legacy ERP field-level mappings
o Transformation rules and standardization logic
o Handling of missing/invalid data<ul><li>Define Data Cleansing &amp; Preparation Plan:</li></ul>
o Deduplication rules
o Data enrichment where required
o Validation checkpoints before migration<ul><li>Design Migration Execution Plan:</li></ul>
o Migration cycles (mock runs, dry runs, final cutover)
o Rollback strategy in case of failure
o Downtime and cutover planning<ul><li>Define Data Validation &amp; Reconciliation Framework:</li></ul>
o Pre-migration vs post-migration validation rules
o Reconciliation reports (counts, totals, relationships)
o Sign-off criteria for each module<ul><li>Produce key deliverables:</li></ul>
o Data Migration Plan
o Data Mapping Documents
o Data Validation &amp; Reconciliation Reports<ul><li>Identify and enable AI/ML use cases, such as:</li></ul>
o Predictive maintenance modeling
o Inventory demand forecasting
o Supplier performance analytics<ul><li>Leverage AI tools for:</li></ul>
o Data profiling and anomaly detection
o Data quality assessment and cleansing recommendations
o Advanced analytics and insights generation<ul><li>Define enterprise conceptual data model:</li></ul>
o Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs<ul><li>Establish:</li></ul>
o Entity relationships
o Master data definitions
o Data standardization rules<ul><li>Support BI teams for dashboards and analytics</li><li>Align data models with business workflows</li><li>Ensure requirements are data-feasible and consistent</li></ul> 
Requirements 
3. Required Skills &amp; Experience
Mandatory<ul><li> 5 - 8 years in Data Analyst / Data Architecture roles</li><li>Experience in large-scale ERP or enterprise data transformation programs</li><li>Strong expertise in:</li></ul>
o Data modelling (conceptual &amp; logical)
o Data migration and cleansing
o Data warehousing and reporting
Technical Expertise<ul><li>Strong knowledge of:</li></ul>
o ETL processes and migration tools
o SQL and relational databases
o API-based integrations<ul><li>Experience with BI tools (Power BI, Tableau)</li></ul>
Preferred<ul><li>Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)</li><li>Exposure to:</li></ul>
o Maintenance (MRO) data
o Inventory systems
o Technical documentation repositories<ul><li>Demonstrated experience using AI/ML tools or platforms, such as:</li></ul>
o Data analysis and prediction tools
o AI-assisted data modeling or profiling tools<ul><li>Ability to translate data into AI-driven insights for decision-making</li></ul>
Why Join CodeNinja?<ul><li>
Work on impactful ERP transformation projects at enterprise scale
</li><li>Shape end-to-end data strategy, migration, and architecture
</li><li>Leverage AI/ML for advanced data insights and analytics
</li><li>Collaborate with cross-functional teams and drive business decisions
</li><li>Build scalable data models and governance frameworks
</li><li>Grow in a culture of innovation, ownership, and continuous learning</li></ul>
Equal Opportunity Statement
We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply. 
Benefits 
<ul><li>
Provident Fund</li><li>
Gym Membership
</li><li>Leaves as per the company policy
</li><li>Company-paid trips
</li><li>Easy Loan Facility for Employees
</li><li>Yearly increment
</li><li>Maternity Benefits (Leaves &amp; WFH)
</li><li>Health Insurance (Maternity covered) &ndash; includes spouse and parents (till age 80)</li></ul></div>

Data Analyst/Data Architect

CodeNinja Inc.

<div>
 
 About CodeNinja
 
 
 
 
 CodeNinja
 
 is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
 
 
 
 
 Role Purpose
 
 
 
 
 Lead the ERP program's data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Conduct comprehensive assessment of legacy data sources:
 </li>
 <li>
 Inventory, Maintenance (MRO), Procurement, HR, Technical Docs
 </li>
 <li>
 Identify:
 </li>
 <li>
 Data quality issues (duplicates, missing, inconsistencies)
 </li>
 <li>
 Data ownership and governance gaps
 </li>
 <li>
 Redundant/siloed datasets
 </li>
 <li>
 Define data cleansing and standardization approach
 </li>
 <li>
 Produce Data Readiness Assessment Report
 </li>
 <li>
 Define end-to-end Data Migration Strategy, including:
 </li>
 <li>
 Migration approach (phased, module-wise, or big-bang)
 </li>
 <li>
 Data prioritization (master data vs transactional vs historical)
 </li>
 <li>
 Develop Data Mapping Specifications:
 </li>
 <li>
 Legacy &rarr; ERP field-level mappings
 </li>
 <li>
 Transformation rules and standardization logic
 </li>
 <li>
 Handling of missing/invalid data
 </li>
 <li>
 Define Data Cleansing &amp; Preparation Plan:
 </li>
 <li>
 Deduplication rules
 </li>
 <li>
 Data enrichment where required
 </li>
 <li>
 Validation checkpoints before migration
 </li>
 <li>
 Design Migration Execution Plan:
 </li>
 <li>
 Migration cycles (mock runs, dry runs, final cutover)
 </li>
 <li>
 Rollback strategy in case of failure
 </li>
 <li>
 Downtime and cutover planning
 </li>
 <li>
 Define Data Validation &amp; Reconciliation Framework:
 </li>
 <li>
 Pre-migration vs post-migration validation rules
 </li>
 <li>
 Reconciliation reports (counts, totals, relationships)
 </li>
 <li>
 Sign-off criteria for each module
 </li>
 <li>
 Produce key deliverables:
 </li>
 <li>
 Data Migration Plan
 </li>
 <li>
 Data Mapping Documents
 </li>
 <li>
 Data Validation &amp; Reconciliation Reports
 </li>
 <li>
 Identify and enable AI/ML use cases, such as:
 </li>
 <li>
 Predictive maintenance modeling
 </li>
 <li>
 Inventory demand forecasting
 </li>
 <li>
 Supplier performance analytics
 </li>
 <li>
 Leverage AI tools for:
 </li>
 <li>
 Data profiling and anomaly detection
 </li>
 <li>
 Data quality assessment and cleansing recommendations
 </li>
 <li>
 Advanced analytics and insights generation
 </li>
 <li>
 Define enterprise conceptual data model:
 </li>
 <li>
 Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs
 </li>
 <li>
 Establish:
 </li>
 <li>
 Entity relationships
 </li>
 <li>
 Master data definitions
 </li>
 <li>
 Data standardization rules
 </li>
 <li>
 Support BI teams for dashboards and analytics
 </li>
 <li>
 Align data models with business workflows
 </li>
 <li>
 Ensure requirements are data-feasible and consistent
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Required Skills &amp; Experience
 
 
 </li>
 </ul>
 
 Mandatory
 
 
 
 <ul>
 <li>
 5 - 8 years in Data Analyst / Data Architecture roles
 </li>
 <li>
 Experience in large-scale ERP or enterprise data transformation programs
 </li>
 <li>
 Strong expertise in:
 </li>
 <li>
 Data modelling (conceptual &amp; logical)
 </li>
 <li>
 Data migration and cleansing
 </li>
 <li>
 Data warehousing and reporting
 
 
 </li>
 </ul>
 
 Technical Expertise
 
 
 
 <ul>
 <li>
 Strong knowledge of:
 </li>
 <li>
 ETL processes and migration tools
 </li>
 <li>
 SQL and relational databases
 </li>
 <li>
 API-based integrations
 </li>
 <li>
 Experience with BI tools (Power BI, Tableau)
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)
 </li>
 <li>
 Exposure to:
 </li>
 <li>
 Maintenance (MRO) data
 </li>
 <li>
 Inventory systems
 </li>
 <li>
 Technical documentation repositories
 </li>
 <li>
 Demonstrated experience using AI/ML tools or platforms, such as:
 </li>
 <li>
 Data analysis and prediction tools
 </li>
 <li>
 AI-assisted data modeling or profiling tools
 </li>
 <li>
 Ability to translate data into AI-driven insights for decision-making
 
 
 </li>
 </ul>
 
 Why Join CodeNinja?
 
 
 
 <ul>
 <li>
 Work on impactful ERP transformation projects at enterprise scale
 </li>
 <li>
 Shape end-to-end data strategy, migration, and architecture
 </li>
 <li>
 Leverage AI/ML for advanced data insights and analytics
 </li>
 <li>
 Collaborate with cross-functional teams and drive business decisions
 </li>
 <li>
 Build scalable data models and governance frameworks
 </li>
 <li>
 Grow in a culture of innovation, ownership, and continuous learning
 
 
 </li>
 </ul>
 
 Equal Opportunity Statement
 
 
 
 We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Provident Fund
 </li>
 <li>
 Gym Membership
 </li>
 <li>
 Leaves as per the company policy
 </li>
 <li>
 Company-paid trips
 </li>
 <li>
 Easy Loan Facility for Employees
 </li>
 <li>
 Yearly increment
 </li>
 <li>
 Maternity Benefits (Leaves &amp; WFH)
 </li>
 <li>
 Health Insurance (Maternity covered) - includes spouse and parents (till age 80)
 </li>
 </ul>
</div>

MILAHA

<div>Communication
 
Internal Communication:
 
Internal Business Units
 
All Internal Department
 
Senior Leadership Team
 
Purpose:
 
 Innovation in AI Products and Services
 
 Customer Experience Enhancement:
 
 Data Integration and Democratization
 
 Predictive and Prescriptive Analytics
 
 Change Management and Adoption of AI
 
 Cloud and Scalable AI Infrastructure
 
 Data Governance and Ethics
External Communication:
 
External IT Vendors
 
Software Integrators
Occupational Health &amp; Safety and Environment
 
Accountability:
 
Are accountable for their acts and omissions.
 
Responsibility:
 
To follow agreed safe systems of work; to follow training and instructions; and to report accidents, incidents and near misses.
 
Authority:
 
To stop work if they think the work is unsafe.</div>
 <div><div>Education &amp; Professional Qualification:
 
Bachelor&rsquo;s Degree in Computer Science, Data Science
 
Artificial Intelligence, Statistics, Mathematics, Engineering, Information Technology
 
Master&rsquo;s Degree (preferred):
 
Data Science, Artificial Intelligence or Machine Learning, Computer Science, Business Analytics, Statistics or Applied Mathematics, Operations Research
 
Professional Experience:
 
<ul><li>8 years of hands-on experience in data science, machine learning, or AI roles, including developing and deploying AI models and algorithms.
</li><li>Experience with machine learning techniques, such as:
</li><li>Supervised/Unsupervised Learning
</li><li>Deep Learning (e.g., Neural Networks, CNNs, RNNs)
</li><li>Natural Language Processing (NLP)
</li><li>Computer Vision
</li></ul>Geographic Experience:
 
A plus
 
Computer Skills:
 
data science, machine learning, AI, including developing and deploying AI models and algorithms
 
Language Skills:
 
Business fluent English
 
Arabic Language is an advantage.</div></div>
 <div><div>Strategic Leadership &amp; Vision
 
<ul><li>Define and execute the organization&rsquo;s Data Science &amp; AI strategy in alignment with business goals.
</li><li>Identify and prioritize opportunities where AI and data driven solutions enhance efficiency, customer experience, product offerings, and revenue generation.
</li><li>Lead the design of a unified data and AI architecture, including the development of a scalable Data Lakehouse, semantic layers, feature stores, and streaming/batch data integration.
</li><li>Drive the Generative AI roadmap&mdash;selecting LLM providers, designing RAG architectures, and enabling enterprise wide AI capabilities.
</li><li>Oversee FinOps practices to optimize cloud and compute costs associated with AI, GPU workloads, and large scale data storage.
</li></ul>AI &amp; Data Engineering Execution
 
<ul><li>Oversee the end to end development, validation, deployment, and lifecycle management of machine learning and AI models.
</li><li>Implement CI/CD/CT pipelines to ensure automated, continuous, and reliable model updates.
</li><li>Build and maintain vector database infrastructure to support semantic search, contextual AI, and long term knowledge retrieval.
</li><li>Ensure data pipelines, platforms, and architectures are optimized for performance, scalability, and resilience.
</li></ul>Governance, Risk, Compliance &amp; Ethics
 
<ul><li>Implement data governance, security, and privacy standards, including RBAC/ABAC and protection of PII and sensitive datasets.
</li><li>Establish and monitor automated controls for model drift, fairness, explainability, and ethical use of AI.
</li><li>Ensure compliance with relevant regulations (e.g., GDPR, HIPAA) and internal policies.
</li><li>Maintain best practices for data quality, versioning, reproducibility, and auditability.
</li></ul>Innovation &amp; Continuous Improvement
 
<ul><li>Lead experimentation with new algorithms, methods, and technologies to maintain a cutting edge AI ecosystem.
</li><li>Promote a culture of continuous improvement, refining processes, tools, and models to enhance performance and business impact.
</li></ul>Team Leadership &amp; Capability Building
 
<ul><li>Mentor and develop a high performing team of data scientists, AI engineers, and data professionals.
</li><li>Oversee training and upskilling initiatives to ensure the team remains current with emerging technologies and methodologies.
</li></ul>Stakeholder Management &amp; Communication
 
<ul><li>Serve as a strategic advisor between business and technical teams&mdash;translating business challenges into AI solutions and articulating AI outcomes clearly to non technical stakeholders.
</li><li>Provide regular updates to leadership on progress, performance metrics, model outcomes, and business results.
</li><li>Drive cross department collaboration to ensure successful adoption and integration of AI solutions.
</li></ul>Technology, Tools &amp; Vendor Management
 
<ul><li>Lead the selection, integration, and management of AI platforms, data tools, and vendor partnerships.
</li><li>Manage budgets for data science and AI initiatives, ensuring optimal allocation of resources.
</li><li>Make decisions related to hiring, vendor selection, and solutions procurement that support strategic AI objectives.</li></ul></div></div>
 <div><div>Education &amp; Professional Qualification:
 
Bachelor&rsquo;s Degree in Computer Science, Data Science
 
Artificial Intelligence, Statistics, Mathematics, Engineering, Information Technology
 
Master&rsquo;s Degree (preferred):
 
Data Science, Artificial Intelligence or Machine Learning, Computer Science, Business Analytics, Statistics or Applied Mathematics, Operations Research
 
Professional Experience:
 
<ul><li>8 years of hands-on experience in data science, machine learning, or AI roles, including developing and deploying AI models and algorithms.
</li><li>Experience with machine learning techniques, such as:
</li><li>Supervised/Unsupervised Learning
</li><li>Deep Learning (e.g., Neural Networks, CNNs, RNNs)
</li><li>Natural Language Processing (NLP)
</li><li>Computer Vision
</li></ul>Geographic Experience:
 
A plus
 
Computer Skills:
 
data science, machine learning, AI, including developing and deploying AI models and algorithms
 
Language Skills:
 
Business fluent English
 
Arabic Language is an advantage.</div></div>

Specialist - AI & Data Architect

Radinnova

Position OverviewWe are seeking an experienced Data Warehouse Architect to design, build, and evolve our enterprise data platform. This role is central to unifying data across our organization's critical business domains &mdash; including Order to Cash (O2C), Procure to Pay (P2P), and Finance Record to Report (R2R) &mdash; into a scalable, governed, and performant data warehouse. The ideal candidate brings deep expertise in enterprise data modeling, modern cloud data platforms, and hands-on experience integrating data from both large-scale ERP systems and niche industry platforms.Key ResponsibilitiesData Architecture &amp; Modeling<ul><li>Design and own enterprise-grade dimensional and relational data models across core business domains: Order to Cash (O2C), Procure to Pay (P2P), and Finance Record to Report (R2R)</li><li>Develop and maintain conceptual, logical, and physical data models aligned to business process frameworks (e.g., APQC, SAP reference models)</li><li>Establish and enforce data modeling standards, naming conventions, and architectural best practices across the organization</li><li>Define and manage data domains, subject areas, and data products to support self-service analytics and enterprise reporting</li></ul>Data Pipeline &amp; Integration<ul><li>Architect and oversee end-to-end data pipelines &mdash; ingestion, transformation, orchestration, and delivery &mdash; for batch and near-real-time workloads</li><li>Lead the integration of structured and semi-structured data from ERP and operational systems into the data warehouse</li><li>Evaluate, select, and implement ETL/ELT tools and frameworks appropriate to the platform stack</li><li>Ensure pipeline reliability, observability, and scalability through monitoring, alerting, and automated testing practices</li></ul>Cloud Platform Engineering<ul><li>Architect and manage cloud-based data warehouse environments on Microsoft Fabric and/or AWS (Redshift, Glue, S3, Lake Formation, or equivalent)</li><li>Design lakehouse and medallion architectures (Bronze / Silver / Gold) where appropriate</li><li>Optimize platform performance, cost, and security in alignment with enterprise cloud governance standards</li></ul>ERP &amp; Source System Integration<ul><li>Lead data extraction and mapping from enterprise ERP platforms, like SAP including complex financial, procurement, and sales modules</li><li>Integrate data from niche and industry-specific ERP platforms including Clipboard K8 and Stone Profit System</li><li>Collaborate with ERP functional teams to understand business processes, data flows, and source-system data quality characteristics</li><li>Document source-to-target mappings and maintain data lineage across all integrated systems</li></ul>Governance &amp; Quality<ul><li>Define and implement data governance frameworks, including data ownership, stewardship, and quality rules across integrated domains</li><li>Partner with data governance and compliance teams to ensure data accuracy, completeness, and auditability &mdash; especially for financial reporting (R2R)</li><li>Implement and maintain master data management (MDM) principles for key entities such as customers, vendors, and chart of accounts</li></ul>Leadership &amp; Collaboration<ul><li>Serve as the technical lead and subject matter expert for all data warehouse and data modeling initiatives</li><li>Mentor and guide data engineers and analysts on architecture standards and best practices</li><li>Partner with business stakeholders across Finance, Supply Chain, and Operations to translate requirements into scalable data solutions</li><li>Engage with vendors, consultants, and third-party data providers as needed</li></ul>Required Qualifications<ul><li>5&ndash;10 years of progressive experience in data warehousing, data architecture, or data engineering roles</li><li>Proven expertise designing enterprise data models for Order to Cash, Procure to Pay, and/or Finance Record to Report business domains</li><li>Strong proficiency in SQL and experience with dimensional modeling (Kimball, Inmon) and modern data vault methodologies</li><li>Hands-on experience building and managing data pipelines using tools such as dbt, Azure Data Factory, AWS Glue, Apache Airflow, or similar</li><li>Demonstrated experience with cloud data platforms &mdash; Microsoft Fabric and/or AWS (Redshift, S3, Glue, Athena, etc.)</li><li>Meaningful experience integrating data from SAP including financial, logistics, and procurement modules</li><li>Solid understanding of data governance, data quality frameworks, and metadata management</li></ul>Preferred Qualifications<ul><li>Experience with niche ERP platforms including Clipboard K8 and/or Stone Profit System</li><li>Familiarity with Microsoft Fabric components: OneLake, Lakehouse, Data Pipelines, and Semantic Models</li><li>AWS certifications (e.g., AWS Certified Data Analytics &ndash; Specialty) or Microsoft certifications (e.g., DP-700 Fabric Analytics Engineer)</li><li>Experience with BI and reporting platforms such as Power BI, Tableau, or Phocas</li><li>Background in financial close processes, revenue recognition, or supply chain operations</li><li>Familiarity with data catalog and lineage tools (e.g., Purview, Alation, Collibra)</li><li>Experience with real-time or streaming data architectures (Kafka, Kinesis, Event Hubs)</li></ul>Work Location: Hybrid remote in Livonia, MI 48150

Data Warehouse Architect

University of Wisconsin–Madison

<div>Current employees: if you are currently employed at any of the universities of wisconsin, log in to workday to apply through the internal application process.
Job category:
Academic Staff
Employment type:
Regular
Job profile:
Technical Integration Eng III
Job summary:<div>
<div>
The Wisconsin Health Data Hub (WHDH), funded by the U.S. Economic Development Administration (EDA), is developing a secure, cloud-native data platform designed to deliver high-quality real-world data to support biomedical research, advanced analytics, and AI-driven discovery.

</div><div>The Data Solutions Architect provides senior technical leadership responsible for designing, implementing, and governing the architecture of WHDH&rsquo;s data platform. This role ensures the secure, scalable integration, storage, and analysis of complex clinical and research data assets across a cloud-based environment. The position supports advanced analytics, machine learning, and federated research capabilities while maintaining compliance with HIPAA and institutional data governance standards.

</div><div>Working closely with data engineers, AI specialists, security analyst, and governance leaders, the Data Solutions Architect will translate research and operational requirements into scalable data architecture solutions that support WHDH&rsquo;s long-term platform strategy.

</div><div>Key Responsibilities:
</div><div>Data Architecture and Platform Design</div>
<div><ul>
<li>Design and implement the architectural framework supporting WHDH&rsquo;s secure, cloud-native data platform.
</li><li>Develop scalable architectures for ingesting, harmonizing, storing, and delivering structured and unstructured health data.
</li><li>Establish data models, metadata frameworks, and integration architectures that support advanced research workflows.
</li><li>Design high-performance analytics capabilities enabling AI, machine learning, and large-scale data analysis.</li>
</ul></div>
<div>Data Integration and Interoperability</div>
<div>
<ul><li>Architect secure data pipelines for ingestion and transformation of multi-source clinical and research datasets.
</li><li>Enable interoperable data exchange across contributing health systems and research institutions.</li>
<li>Implement scalable services supporting federated queries, distributed analytics, and secure data sharing.
</li></ul></div><div>Data Governance and Security</div>
<div><ul>
<li>Ensure compliance with HIPAA, institutional governance policies, and research data security standards.
</li><li>Establish architectural best practices related to data governance, reproducibility, and responsible use of sensitive health data.</li>
<li>Design solutions that support secure access control, auditing, and governance across the WHDH data ecosystem.</li>
</ul></div>
</div><div><div>Platform Innovation and Strategy
</div>
<div><ul><li>Guide the adoption of modern data platform architecture that enhance data discovery, metadata management, and scalable research workflows.
</li><li>Evaluate and implement emerging trends that improve interoperability, accessibility, and performance of WHDH data assets.</li>
<li>Develop modular, extensible platform components that enable technology transfer and sustainability beyond the grant period.</li>
</ul></div>
<div>Collaboration and Leadership
</div>
<div><ul><li>Collaborate with cross-functional teams including data engineers, AI researchers, security analyst, and governance leaders.
</li><li>Provide leadership in defining system design patterns and platform architecture standards.
</li><li>Support multi-institutional research initiatives by enabling secure and scalable collaborative data environments.
</li></ul></div><div>It is anticipated that this position will be remote and requires work be performed at an offsite, non-campus work location. It is an expectation the finalist will have permanent residence within the State of Wisconsin. Successful applicants who do not currently live in Wisconsin must have plans to move to the State within a reasonable time from the position start date.
</div>
</div>Key job responsibilities:<ul><li>
Develops architectural patterns that support large-scale biomedical datasets, including real-world data, clinical text, imaging, and genomic data, enabling advanced analytics, machine learning, and AI-driven research workflows within a secure cloud environment</li></ul><ul><li>
Designs and implements data architecture that enables secure ingestion, normalization, and integration of clinical, research, and operational data from multiple health system partners while ensuring compliance with HIPAA, institutional policies, and data use agreements</li></ul><ul><li>
Participates in the evaluation of vendor software releases, upgrade planning, and impact. Documents and communicates system enhancements or changes</li></ul><ul><li>
Integrates, identifies, troubleshoots, monitors, and resolves complex and varied supported services, systems, network, and application problems according to established processes and procedures</li></ul><ul><li>
Assists in the design of system and infrastructure specifications, implementation, and/or integration, trend analysis, and capacity planning</li></ul><ul><li>
Designs small components and runs, maintains, and operates technical systems and infrastructure</li></ul><ul><li>
Plans, coordinates, and executes the development, testing, implementation, integration, and installation of moderately complex system resources, upgrades, and security components in alignment with industry best practices</li></ul><ul><li>
Defines and implements standards for healthcare data interoperability using frameworks such as HL7 FHIR, OMOP Common Data Model, and other biomedical data models to ensure consistent, high-quality data exchange across contributing institutions and research partners</li></ul><ul><li>
Serves as an expert point of contact for external stakeholders and IT partners regarding system integrations, identifies needs, provides solution options, and communicates issue updates and resolutions</li></ul><ul><li>
Plans and directs staff implementation of small to medium technical projects as needed</li></ul><ul><li>
Architects systems that enable privacy-preserving analytics, federated queries, and secure multi-institutional collaboration while maintaining strict data governance controls and enabling authorized researchers to discover and analyze distributed health datasets</li></ul><h1 class="jobSectionHeader">
Department:</h1>
School of Medicine and Public Health, Office of Informatics and Information Technology, Wisconsin Health Data Hub.
This position is within the School of Medicine and Public Health&rsquo;s Office of Informatics and Information Technology (IIT). IIT is a multidisciplinary team of data scientists, engineers, developers, and IT support staff. We offer a variety of Informatics and IT services to departments and research staff within the School of Medicine and Public Health and beyond to support the conduct of high-quality clinical and translational research.<ul>
<li>
Informatics: We provide innovative solutions and training for a broad spectrum of clinical and translational research utilizing real-world data to facilitate rapid translation of research findings into clinical practice, with an emphasis on precision medicine, healthcare delivery, and population health.</li>
<li>
Technology Solutions: We provide technology solutions to the School of Medicine and Public Health including cybersecurity, educational technology, and IT support.</li>
</ul><h1 class="jobSectionHeader">
Compensation:</h1>
The starting salary for the position is $110,000 annually, but is negotiable based on experience and qualifications.<div>
Employees in this position can expect to receive benefits such as generous vacation, holidays, and sick leave; competitive insurances and savings accounts; retirement benefits.</div><h1 class="jobSectionHeader">
Required Qualifications:</h1><div><ul>
<li>At least 3 years' experience designing and implementing enterprise-scale data architectures; 5 years' preferred
</li><li>Expertise with cloud-native data platforms and distributed data solutions.</li>
<li>Experience designing secure data pipelines and large-scale data integration frameworks.
</li><li>Familiarity with healthcare or biomedical research data environments and relevant regulatory requirements.</li>
</ul></div><h1 class="jobSectionHeader">
Preferred Qualifications:</h1><div><ul>
<li>Experience with healthcare data standards and interoperability frameworks.</li>
<li>Experience supporting AI/ML and advanced analytics workloads.</li>
<li>Expertise with federated data architectures and secure multi-institutional data collaboration.
</li><li>Experience working in federally funded research programs or academic research environments.</li>
<li>Strong documentation and technical leadership skills
</li></ul></div><h1 class="jobSectionHeader">Education:</h1><ul><li>
Bachelor's degree preferred; focus in Computer Science, Information Systems, Data Engineering, or related field preferred.</li></ul><h1 class="jobSectionHeader">
How to Apply:</h1><div>

For the best experience completing your application, we recommend using Chrome or Firefox as your web browser.
To apply for this position, select either &ldquo;I am a current employee&rdquo; or &ldquo;I am not a current employee&rdquo; under Apply Now. You will then be prompted to upload your application materials.
</div><div>
Important: The application has only one attachment field. Upload the following documents in that field, either as a single combined file or as multiple files in the same upload area.
<ul>
<li>Cover letter</li>
<li>Resume</li>
</ul>
Your cover letter should address how your training and experience aligns with the required and preferred qualifications listed above. Application reviewers will rely on these written materials to determine which applicants move forward in the process. References will be requested from final candidates. All applicants will be notified once the search concludes and a candidate is selected.
</div><div>
University sponsorship is not available for this position, including transfers of sponsorship and TN visas. The selected applicant will be responsible for ensuring their continuous eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of appointment. This position is an ongoing position that will require continuous work eligibility. If you are selected for this position you must provide proof of work authorization and eligibility to work.

The department will not be able to support a request for a J-1 waiver. If you choose to pursue a waiver and apply for our position, neither the UW nor UWMF will reimburse you for your legal or waiver fees.
</div><h1 class="jobSectionHeader">
Contact Information:</h1><div>
Cody Roekle, croekle@wisc.edu, 16082637676</div><div>
Relay Access (WTRS): 7-1-1. See RELAY_SERVICE for further information.
</div>Institutional statement on diversity:
Diversity is a source of strength, creativity, and innovation for UW-Madison. We value the contributions of each person and respect the profound ways their identity, culture, background, experience, status, abilities, and opinion enrich the university community. We commit ourselves to the pursuit of excellence in teaching, research, outreach, and diversity as inextricably linked goals. 
 
The University of Wisconsin-Madison fulfills its public mission by creating a welcoming and inclusive community for people from every background - people who as students, faculty, and staff serve Wisconsin and the world. 
The University of Wisconsin-Madison is an Equal Opportunity Employer.
Qualified applicants will receive consideration for employment without regard to, including but not limited to, race, color, religion, sex, sexual orientation, national origin, age, pregnancy, disability, or status as a protected veteran and other bases as defined by federal regulations and UW System policies. We promote excellence by acknowledging skills and expertise from all backgrounds and encourage all qualified individuals to apply.
To request a disability or pregnancy-related accommodation for any step in the hiring process (e.g., application, interview, pre-employment testing, etc.), please contact the Divisional Disability Representative (DDR) in the division you are applying to. Please make your request as soon as possible to help the university respond most effectively to you.
Employment may require a criminal background check. It may also require your references to answer questions regarding misconduct, including sexual violence and sexual harassment. 
 
The University of Wisconsin System will not reveal the identities of applicants who request confidentiality in writing, except that the identity of the successful candidate will be released. See Wis. Stat. sec. 19.36(7). 
 
The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. UW-Madison will provide a paper copy upon request; please contact the University of Wisconsin Police Department.</div>

WHDH Data Solutions Architect

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