Sr. Data Engineer(Capital Markets/CCAR)

Euclid Innovations

  • Charlotte, NC
  • 11 days ago

    Highlights

    Design, develop, and maintain scalable data pipelines and data platforms supporting CCAR, stress testing, capital planning, and regulatory reporting initiatives. Strong experience with Azure Cloud technologies, including Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and cloud-based data architecture.

    Numbers & Facts

    LocationCharlotte, NC

    Description

    Role: Sr. Data Engineer(Capital Markets/CCAR)\
    Duration: Long Term Contract
    Location: Charlotte, NC(Hybrid, Onsite 3 Days/Week)

    Objective: Build and support a centralized regulatory reporting data platform from EOD Price/Position sources through Risk and Federal Reporting.

    Scope of Work:

    High Level Data Flow: EOD Price/Position > CM/Nikko > Data Store > Analysis > Risk > Fed Reporting

    • End-to-end data pipelines (ingestion, transformation, validation)
    • Data models for centralized data flows
    • Historical data onboarding and reconciliation from external data sources
    • Data quality controls and monitoring frameworks
    • Documentation including design, data lineage, and controls
    • Integration with upstream and downstream systems
    • Support for regulatory requirements including CCAR

    Key Responsibilities & Experience Required:

    • Design, develop, and maintain scalable data pipelines and data platforms supporting CCAR, stress testing, capital planning, and regulatory reporting initiatives.
    • Strong experience with Azure Cloud technologies, including Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and cloud-based data architecture.
    • Hands-on expertise with Azure Data Factory (ADF) for data ingestion, orchestration, workflow automation, and monitoring of enterprise data pipelines.
    • Experience building and optimizing large-scale data processing solutions using Databricks, Apache Spark, and Delta Lake.
    • Strong programming and data manipulation skills using Python and SQL for data transformation, validation, reconciliation, and analytics.
    • Familiarity with DevOps practices, including CI/CD, automation, version control, testing, and deployment processes, with the ability to work effectively across Risk, Finance, and Technology teams.

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