• Create and edit logical and physical data models, XML schemas, and file formats using ER/Studio, XML Spy, or equivalent tools. • Build tables, define columns and data types, and perform database scripting (DDL, inserts, updates, data movement). • Analyze and profile data sources; develop source-to-target mappings with detailed transformations and business rules using Erwin Mapping Manager or similar. • Collaborate with business and technical stakeholders to define transformation rules and data flow, ensuring mapping rules and data governance are followed. • Write SQL scripts to analyze, validate, or correct data, including complex stored procedures, views, and functions. • Monitor data quality, investigate issues, and execute remediation plans. • Provide guidance to teams on solutions, enterprise architecture best practices, and standards. • Review project deliverables for quality and compliance; recommend improvements.

• Develop and optimize PySpark-based ETL pipelines for processing large-scale data • Develop, test, and maintain robust Python applications • Collaborate with data engineers, analysts, and other developers to design and implement data solutions • Work with Azure Data Lake, Azure Databricks, and Azure Data Factory to build scalable data solutions • Implement data classification, policy enforcement, and metadata extraction within Purview • Collaborate with data engineers and business teams to ensure smooth data flow across systems • Troubleshoot performance bottlenecks in Spark jobs and improve data pipeline efficiency • Ensure data security, compliance, and quality following best practices.

• Perform Data Warehouse Architecture at an intermediate level • Focus on design and development of data models and ETL specifications • Conduct data analysis, system design and architecture, standards and policy administration • Coordinate vendor relations and conduct product/vendor research • Create moderate to advanced data models and ETL specifications • Maintain documentation on design and operation • Analyze data sources and recommend solutions • Participate in long-term data warehouse and dashboard architecture planning • Manage existing systems compliance with established standards

• Develop repeatable ETL pipelines to feed team dashboards, reports, and analytics • Investigate underlying data to assist in production support efforts • Assist platform engineering team with in-app reporting and dashboard development • Work with adjacent teams to develop reliable data extracts that support their work • Implement validation checks and monitoring to maintain data integrity and consistency • Build tools to fabricate data sets for standing up product demos and to assist QA efforts • Perform other duties as assigned