Senior Data Engineer - Databricks

Dataeconomy

  • Raleigh, North Carolina
  • 4 days ago

    Highlights

    Full-time Build scalable, production-grade ETL/ELT pipelines using Databricks (PySpark, Spark SQL, Delta Live Tables, Workflows). We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.

    Numbers & Facts

    LocationRaleigh, North Carolina
    Websitehttps://www.dataeconomy.ai

    Description

    DATAECONOMY is one of the fastest-growing Data & Analytics company with global presence. We are well-differentiated and are known for our Thought leadership, out-of-the-box products, cutting-edge solutions, accelerators, innovative use cases, and cost-effective service offerings.
     
    We offer products and solutions in Cloud, Data Engineering, Data Governance, AI/ML, DevOps and Blockchain to large corporates across the globe. Strategic Partners with AWS, Collibra, cloudera, neo4j, DataRobot, Global IDs, tableau, MuleSoft and Talend.

    Senior/Lead Data Engineer — Databricks

    Raleigh NC

    Full-time
    • Build scalable, production-grade ETL/ELT pipelines using Databricks (PySpark, Spark SQL, Delta Live Tables, Workflows).
    • Ingest structured, semi-structured, and streaming data into Bronze, Silver, and Gold layers.
    • Develop optimized transformations, data quality rules, and reusable framework components.
    • Implement best practices for job orchestration, monitoring, alerting, and automation.
    • Hands-on experience: Spark, Delta Lake, Workflows, Unity Catalog.
    • Strong SQL programming and performance tuning skills.
    • Experience with cloud environments (AWS/Azure/GCP).
    • Experience with modern data lakehouse concepts and distributed systems.
    • Strong understanding of Lakeflow Connect, LSDP/Lakehouse, Medallion Architecture, Data Validations, Genie, and Agent Bricks/RAG use cases.
    • Should be able to explain these concepts using real project examples and architecture decisions.


    Requirements

    •  Strong Python (PySpark) and SQL programming
    •  Databricks — Spark, Delta Lake, Workflows, Unity Catalog
    •  ETL/ELT pipeline development — Medallion Architecture (Bronze/Silver/Gold)
    •  Delta Live Tables, Auto-Loader, Structured Streaming
    •  Data modeling — dimensional (star/snowflake), normalization/denormalization
    •  CI/CD, Git, job orchestration
    •  Cloud experience — AWS, Azure, or GCP
    •  7–10+ years in data engineering

    Nice-to-Have Skills

    •  Lakeflow Connect, LSDP/Lakehouse, Genie, Agent Bricks/RAG use cases
    •  Data governance, metadata management, Unity Catalog advanced features
    •  Airflow, dbt, or similar orchestration tools
    •  Data security, compliance, and access models
    •  Cost optimization and performance tuning in cloud environments
    •  Corporate/enterprise data warehousing background


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