[Hiring] Lead IT QA Analyst @Assurant

Role Description

• Validate enterprise BI solutions aligned to Kimball dimensional modeling (facts, dimensions, conformed dimensions, SCD handling).
• Work with business teams to confirm business rules, acceptance criteria, KPIs, and reconciliation logic for BI/analytics outputs.
• Perform end to end QA across ingestion → transformation → semantic layer → reporting/consumption.
• Analyze TPA client files and record variances.
• Define QA standards, guidelines, and best practices for analytics engineering and reporting teams.
• Use AI tools to build test cases, test data and testing plans wherever applicable.
• Create and maintain test frameworks for:
  • Data correctness (row counts, aggregates, null handling, duplicates)
  • Business rule validation (KPI logic, exclusions, thresholds)
  • Regression testing (pipeline and reporting changes)
  • Data reconciliation (source to target, cross system checks)
• Automate QA activities wherever possible to reduce manual effort and improve release velocity.
• Validate Databricks pipelines (Delta tables, notebooks, jobs, workflows) and SQL transformations (Spark SQL / T-SQL).
• Perform QA of ETL/ELT patterns including incremental loads, CDC patterns, and partitioning strategies.
• Validate SQL Server objects such as stored procedures, views, tables, indexing strategies, and job schedules where applicable.
• Execute performance testing for Databricks jobs and SQL Server queries (query tuning, indexing suggestions, cluster sizing guidance).
• Recommend strategies to improve platform performance, cost efficiency, and workload stability.
• Provide support for production execution and delivery of BI/analytics solutions.
• Support platform upgrades and migrations (Databricks runtime upgrades, cluster policies, SQL Server version changes) in dev/test, including QA sign off and documentation.
• Maintain accurate and complete QA documentation: test plans, test evidence, defect logs, reconciliation results.
• Ensure adherence to corporate policies, governance, and established practices.
• Mentor team members on QA methods, automation, and data validation patterns.

Company Description