
Senior Data Engineer - Databricks
Required skills
- Databricks
- PySpark
- Spark SQL
- Delta Live Tables
- Delta Lake
- Unity Catalog
- SQL
- Python
- ETL/ELT
- Medallion Architecture
Nice to have
- Lakeflow Connect
- LSDP/Lakehouse
- Genie
- Agent Bricks/RAG
- Data governance
- metadata management
Role summary
DATAECONOMY, a fast-growing Data & Analytics company, seeks a Senior/Lead Data Engineer specializing in Databricks. The role involves building scalable ETL/ELT pipelines, ingesting various data types, developing transformations, and implementing best practices for orchestration and monitoring. Key technologies include Databricks (PySpark, Spark SQL, Delta Live Tables, Workflows), Delta Lake, Unity Catalog, SQL, Python, and cloud environments (AWS/Azure/GCP). Experience with data lakehouse concepts, Medallion Architecture, and CI/CD is required. Nice-to-have skills include advanced data governance, orchestration tools like Airflow/dbt, and cost optimization.
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
- 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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