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 fast 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 contemporary 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 [email protected]

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