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

- Great 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.

- Quick-track learning with exposure to multi-industry data ecosystems.

- Quarterly performance bonuses tied to QA automation impact metrics.

Skills: snowflake,python,sql

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