Data QA/QR (Quality Review)

Title - Data QA/QR (Quality Review) Location - Alpharetta, GA/ Nashville, TN / Columbus, GA - Hybrid Duration - 12+ months with potential to hire Top 3 Required Skills 1. Experience as a Data QA/QR in a financial services organization within the past 5 years (ideally within the last 3 years). 2. Databricks Overview of project/skills required: • Serve as an independent QA / Quality Review (QR) resource providing effective challenge over the Enterprise Data Mart build on Databricks. • The role focuses on validating data mappings, transformation logic, and end-to-end data integrity prior to Lending and Retail LOB consumption. • They are building a new building in Buckhead (alternate GEOs are Nashville and Columbus GA) • Merger between Synovus and Pinnacle . Work to be completed March 2027 and beyond Key Responsibilities • Review source-to-target mappings, data models, and transformation logic for completeness, accuracy, and alignment to business intent • Execute SQL-based validation and reconciliation across source, curated, and consumption layers • Perform completeness, accuracy, reasonableness, and threshold checks on critical data elements • Identify data gaps, anomalies, undocumented assumptions, and logic defects; document findings clearly • Partner with data engineers and product owners to remediate issues prior to release • Support go-live readiness decisions for Lending and Retail data products Required Experience • Strong hands-on SQL experience (ability to independently query, reconcile, and validate large datasets) • Experience reviewing data mappings, transformation rules, and data pipelines (Databricks / Spark-based environments preferred) • Familiarity with financial services data (Lending, Retail Banking, or Enterprise data domains) • Ability to operate independently and challenge constructively without slowing delivery • Serve as an independent QA / Quality Review (QR) resource providing effective challenge over the Enterprise Data Mart build on Databricks. • The role focuses on validating data mappings, transformation logic, and end-to-end data integrity prior to Lending and Retail LOB consumption. Nice to Have: Experience with systems like FIS, Finastra are helpful (not Jack Henry)

Created: 2026-03-04