Quality Assurance Manager (Data & AI)

What This Role Actually IsHands-on QA ManagerFocused on data platforms, pipelines, and AI/ML systemsLeading a small team while still being involved in executionHeavy collaboration with Data Engineering + Data ScienceMust-Haves6–10 years QA experience2+ years leadership / team leadStrong experience with:Data pipelines (ETL/ELT)SQL + data validationAPI testing / distributed systemsExperience working with data platforms, such as:Snowflake / Databricks / BigQuery / Redshift / Hadoop / SparkExposure to AI/ML concepts (does NOT need to be a Data Scientist)Nice-to-HavesData quality tools:Great Expectations / dbt tests / DeequWorkflow orchestration:AirflowCI/CD + test automation frameworksExperience in analytics-heavy or data-driven environmentsWhat They’ll Be DoingLeading QA for:Data pipelines + warehouses/lakesReal-time/streaming dataAI/ML model validation (light testing, not building models)Owning:Data accuracy, validation, reconciliationTest automation strategiesQA integration into CI/CDManaging:QA/data quality engineersDelivery quality + team performanceBenefits:The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan, life insurance, long-term disability insurance, short-term disability insurance, paid parking/public transportation, (paid time , paid sick and safe time , hours of paid vacation time, weeks of paid parental leave, paid holidays annually - AS Applicable)