About the Opportunity
A fast-scaling technology services firm operating in the Enterprise Data & AI quality assurance space, we build trusted, auditable data pipelines and validation frameworks for global clients across fintech, healthcare, and e-commerce. Our Data QA Engineers ensure data integrity, schema compliance, and pipeline reliability at scale—bridging engineering rigor with business logic to prevent downstream failures.

Role & Responsibilities

- Design and execute automated test suites for batch & streaming data pipelines using Python, SQL, and PyTest.
- Validate ETL/ELT workflows for accuracy, completeness, and timeliness across cloud warehouses (Snowflake, BigQuery, Redshift).
- Implement data quality rules (null checks, uniqueness, referential integrity) and monitor drift using Great Expectations or Deequ.




- Collaborate with Data Engineers to identify data gaps and define validation KPIs for pipeline health.
- Integrate QA checks into CI/CD workflows using GitHub Actions or Jenkins to block bad data releases.
- Document data quality standards, test cases, and failure root causes for cross-team transparency.

Skills & Qualifications

- Must-Have
- Python
- SQL
- PyTest
- Excellent Expectations
- Snowflake
- BigQuery
- CI/CD pipelines
- Data validation frameworks
- Preferred
- Deequ
- AWS Glue or Azure Data Factory
- Apache Airflow

Benefits & Culture Highlights

- 100% remote flexibility with core hours aligned to IST.
- Fast-track learning with exposure to multi-industry data ecosystems.
- Quarterly performance bonuses tied to QA automation impact metrics.

📌 Data QA Engineer (India)
🏢 RudraTech It solutions
📍 India