Data Architect / Delivery Lead
PamTen
United States
3 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Microsoft Azure
Computer Programming
Data Architecture
Information Engineering
Data Governance
Extract Transform Load (ETL)
DevOps
Python (Programming Language)
Key Management
Microsoft SQL Server
SQL Azure
+13 more
Software Architecture
Systems Development Life Cycle
Azure Data Lake
SQL Databases
Data Streaming
Data Processing
Azure Data Factory
Snowflake
Data Lakes
Pyspark
Azure Synapse Analytics
Data Pipelines
Databricks
Job description
As a Data Architect / Delivery Lead you will design, build, and manage Azure-based data engineering solutions for healthcare clients, while leading end-to-end delivery, ensuring data quality, governance, and alignment with business requirements.
Requirements
- 10-15+ years of experience in Data Engineering (hands-on delivery roles)
- Experience in Healthcare Payer / Medicaid domain with knowledge of Claims, Member, Provider, Eligibility data and HIPAA/PHI compliance
- Strong Azure-first cloud experience (architecture, implementation, operations)
- Hands-on expertise in Azure services: ADLS Gen2, Azure Databricks, Azure Data Factory (ADF), Azure Synapse, Azure SQL / SQL Server, Azure Key Vault, Azure DevOps (Repos, Pipelines, Boards)
- Strong programming skills in SQL (advanced querying, optimization), Python, PySpark
- Experience building ETL / ELT pipelines and working with batch & streaming data processing
- Strong data modeling experience: conceptual, logical, physical, dimensional (star/snowflake), SCDs, historized data
- Knowledge of Data Lake / Lakehouse architectures, CDC, and incremental data processing
- Ability to review and optimize data models, transformations, and schema evolution
- Experience implementing data governance across Dev/Test/Prod environments
- Exposure to CI/CD pipelines and DevOps practices
- Experience with AI-assisted / Agentic development, including task breakdown, architecture definition, guardrails, and governance
- Understanding of AI-assisted SDLC, security, compliance, auditability, and traceability.
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Prepare application
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