Senior Data Engineer - Databricks

DATAECONOMYRaleigh, NC
Onsite

About The Position

DATAECONOMY is a rapidly growing Data & Analytics company with a global presence, known for its thought leadership, innovative products, cutting-edge solutions, accelerators, and cost-effective service offerings. We specialize in Cloud, Data Engineering, Data Governance, AI/ML, DevOps, and Blockchain, serving large corporations worldwide. We are strategic partners with AWS, Collibra, Cloudera, Neo4j, DataRobot, Global IDs, Tableau, MuleSoft, and Talend.

Requirements

  • 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.
  • 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 Haves

  • 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

Responsibilities

  • 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.
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