We're looking for a Senior Quality Engineer to champion data quality across our data products, analytics workflows, and distributed systems. This is a senior IC role — not people management — partnering directly with developers, data engineers, and analysts to protect data integrity and analytical trust.

What You'll Own:

End-to-end testing strategy for distributed systems, data pipelines, analytics workflows and reporting

Data quality standards — accuracy, completeness, consistency, freshness, lineage, reconciliation

Validation strategy for source-to-target data flows — ingestion, transformation, schema changes, downstream analytics

Automated checks and test frameworks for database, API, and pipeline regression validation

Integration and performance testing for batch, streaming, and near-real-time workflows

Shift-left quality culture — mentoring on testing principles, data contracts, and quick feedback loops

Quality metrics and KPIs tracking data health, pipeline reliability, and defect trends.

What you bring:





✅ 5+ years in software/quality/data/analytics engineering, with deep focus on quality in distributed systems

✅ Hands-on with database validation, data profiling, reconciliation, source-to-target testing

✅ Strong SQL and understanding of relational/non-relational data stores, modeling, schema design

✅ Experience validating dashboards, reports, and business KPIs back to source data

✅ Familiarity with modern data tooling (Snowflake, BigQuery, Databricks, Spark, Airflow, Kafka, Great Expectations, Soda, Monte Carlo, or similar)

✅ Scripting/automation skills (Python, JS/TS, Java, SQL, Bash) and CI/CD experience (GitHub Actions, Azure DevOps, Jenkins, etc.)

✅ Strong systems-thinking and root-cause analysis for complex data/system behaviors

If you see quality as a systems problem, not a checklist — let's talk. Write to

📌 Data Quality Engineer - Global SaaS Product - Hyderabad
🏢 CareerXperts Consulting
📍 Hyderabad