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Senior Data Engineer - Databricks

Dataeconomy · dataeconomy.io
RaleighSenior
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The job in short

Databricks data engineering.

PythonSQLSparkDatabricksAWSAzureGCPDevOpsTableauRAG

Details

Found
33 d ago · posted 2026-09-10
Location
Raleigh, North Carolina

Full 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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