Develop and optimize high-performance, end-to-end data transformation and reporting solutions using PySpark, Spark SQL, and T-SQL within cloud-native environments like Databricks
Architect and implement complex logical and physical data models that support modern patterns such as Data Lakehouse, Data Mesh, and Data Fabric
Construct robust ETL/ELT pipelines that facilitate seamless data ingestion and transformation from diverse sources into production-ready data assets
Build and maintain specialized data structures, including feature stores and automated retraining pipelines, to support the operationalization of machine learning models
Design test strategy, test plan, and test cases
Own and maintain complete and current assigned technical documentation
Collaborate with PMO on project estimation and resourcing