Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python.
Develop and optimize ELT/ETL processes for large-scale data ingestion and transformation.
Implement robust data quality, monitoring, and reconciliation frameworks.
Build reusable data engineering components and frameworks. Data Platform Migration & Modernization
Lead migration of legacy data platforms, data warehouses, and ETL ecosystems to Databricks Lakehouse.
Transform existing ETL workloads to modern ELT patterns using dbt.
Analyze source environments and define migration approaches, roadmap, and execution strategy.
Drive code conversion, performance optimization, and workload modernization efforts.

Databricks Engineering Develop solutions leveraging:

Databricks Lakehouse Platform
Delta Lake
Unity Catalog
Databricks Workflows
Structured Streaming
Medallion Architecture (Bronze, Silver, Gold) Optimize Spark jobs and Databricks workloads for performance and cost efficiency. dbt Development
Build and maintain dbt models, macros, tests, and documentation.
Implement incremental processing and reusable transformation frameworks.
Establish data lineage, testing, and CI/CD best practices.
Work closely with business and analytics teams to build trusted datasets. Leadership & Collaboration
Lead a team of data engineers and developers.
Perform code reviews and enforce engineering standards.
Collaborate with archit ects, produc t owners, business analysts, and stakeholders.
Mentor junior engineers and drive adoption of best practices.

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