Key Responsibilities:

• Design and develop data structures, data models, and transformation processes to support analytics, business intelligence, reporting, and data science initiatives

• Build, maintain, and improve ETL pipelines and data workflows using SQL, Python, Databricks, and related technologies

• Develop scalable data solutions within a Medallion Architecture framework, including Bronze, Silver, and Gold data layers

• Implement data integration processes across multiple transaction systems, operational platforms, and business data sources

• Ensure data accuracy, quality, completeness, and reliability through validation, monitoring, automated reconciliation, and exception-handling processes

• Work closely with BI teams, data scientists, IT teams, and business stakeholders to support reporting, analytics, and advanced data requirements

• Monitor ETL processes, logs, alerts, and pipeline performance, and proactively address issues impacting data availability or reliability

• Develop, optimize, and maintain SQL tables, stored procedures, functions, and transformation logic

• Support data modeling, including star schema design and structures that enable efficient reporting and analytics

• Support Change Data Capture processes and manage Type 2 and Type 3 tables where applicable

• Improve data pipeline performance through indexing, performance tuning, automation, and scalable development practices

• Develop ETL frameworks and notebook-driven solutions using Python and Databricks

• Support Delta Live Tables pipeline development and related Databricks workflows

• Integrate with external systems through API-based data transfers and other structured data exchange methods

• Support Unity Catalog administration, compute cluster configuration, and Databricks workspace standards as needed

• Maintain comprehensive documentation, technical design notes, data lineage information, and version control for all data engineering solutions

• Ensure source control and code management using Git-based practices

• Partner cross-functionally to identify opportunities to improve data availability, quality, governance, and scalability within the GCC model