Snowflake Data Engineer / Technical Lead

Tror AI for everyone

  • Detroit, MI
  • 1 day ago

    Highlights

    The ideal candidate will also have experience with AWS data services, Oracle, PL/SQL, and SQL , along with the ability to work directly with customers to understand requirements, design solutions, and provide technical leadership. We are looking for an experienced Snowflake Data Engineer / Technical Lead with strong hands-on experience in Snowflake, DataStage, and dbt .

    Numbers & Facts

    LocationDetroit, MI

    Description

    Role: Snowflake Data Engineer / Technical Lead
    Location: Michigan, USA
    Experience: 10+ Years

    Job Summary
    We are looking for an experienced Snowflake Data Engineer / Technical Lead with strong hands-on experience in Snowflake, DataStage, and dbt. The candidate should have a strong background in data warehousing, data modeling, ETL development, and modern data engineering.

    The ideal candidate will also have experience with AWS data services, Oracle, PL/SQL, and SQL, along with the ability to work directly with customers to understand requirements, design solutions, and provide technical leadership.
    Key Responsibilities
    • Design, develop, and maintain scalable data pipelines and ETL/ELT solutions.
    • Develop and optimize data solutions using Snowflake, DataStage, and dbt.
    • Design data warehouses, data models, schemas, and transformation processes.
    • Build and maintain complex SQL queries, stored procedures, and data transformation logic.
    • Work with AWS data services, including Aurora, RDS, DMS, and DynamoDB.
    • Develop and support data integration solutions involving Oracle, PL/SQL, and SQL.
    • Perform data migration, integration, transformation, and validation activities.
    • Optimize Snowflake queries, workloads, and data processing for performance and scalability.
    • Collaborate with business and technical stakeholders to understand data requirements.
    • Lead requirement gathering, solution design, technical discussions, and estimations.
    • Provide technical guidance to data engineering teams and review technical solutions.
    • Troubleshoot data pipeline, ETL, database, and production issues.
    • Ensure data quality, reliability, security, and performance across data platforms.
    • Participate in architecture discussions and recommend appropriate data engineering solutions.

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