Senior Data Analyst

As AWAC transitions from a traditional EDW/Cognos environment to a modern Databricks on AWS Lakehouse, we are seeking a Senior Data Analyst who is as comfortable with P&C business logic as they are with technical data structures. You will be the critical link in our data modernization track, ensuring that data moving from legacy sources into our bronze and silver layers is profiled, cleaned, and accurately mapped to support high-priority Power BI reporting.Key Responsibilities :Source-to-Target Mapping (STTM): Create and maintain detailed mapping documents that bridge legacy EDW schemas to the new Databricks Medallion architecture (Bronze & Silver layers).Data Profiling & Discovery: Use SQL and Python to profile source data, identifying anomalies, quality gaps, and transformation logic required for the Reporting-Ready Silver layer. Modernization Liaison: Facilitate the migration of legacy Cognos reports to Power BI, ensuring that P&C business rules (Claims, Underwriting, Policies) are preserved and optimized in the new environment.Subject Matter Expertise: Act as the P&C domain expert to ensure that subject-area specific data (e.g., GWP, Loss Ratios, Premium reserves) is correctly modeled for downstream reporting. Data Validation: Partner with Data Engineers to perform End-to-End validation, ensuring that data in the Power BI reporting layer matches the financial and operational truth of the source systems.Stakeholder Translation: Translate complex business requirements into technical specifications for the Databricks engineering team.Required Skills & Qualifications P&C Insurance Domain Mastery: Deep understanding of Policy, Claims, and Underwriting data. You must understand the why behind the data, not just the where.Databricks & Spark SQL: Hands-on experience navigating Databricks environments, running notebooks, and querying Delta Tables. Technical Toolkit: * Expert SQL: Ability to write complex joins and window functions across disparate systems. Python: Proficient in using Pandas/PySpark for data profiling and cleaning.Power BI & Cognos: Experience with both—specifically in migrating logic from the latter to the former.Legacy Knowledge: Familiarity with SSIS and traditional EDW structures to help reverse engineer existing ETL logic.Documentation: Proven track record of creating high-quality STTMs and data dictionaries that developers can follow without ambiguity.