Senior Data Engineer - Databricks

Raleigh, United States | Posted on 09/10/2026 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. Rutherford, NJ/ Jersey City, NJ 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. 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. Knowledge of medallion architecture, DLT and unity catalog within Databricks.

Requirements

Strong Python (PySpark) and SQL programming Databricks — Spark, Delta Lake, Workflows, Unity Catalog CI/CD, Git, job orchestration Cloud experience — AWS, Azure, or GCP 7–10+ years in data engineering Knowledge of medallion architecture, DLT and unity catalog within Databricks.

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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