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Data Architect / Delivery Lead

PamTen Inc

  • Philadelphia, PA
  • 30+ days ago

    Highlights

    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). 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.

    Numbers & Facts

    LocationPhiladelphia, PA

    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.

    Required:
    • 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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