Data QE

Must Have:

- Experience of driving advanced software testing techniques applying modern automation test approaches in Data Engineering project, ensuring robust data quality
- Hands-on experience of developing BDD based Automation Frameworks for Data, ETL & Event -Driven applications using Python, Java or Typescript
- Ability to solve complex automation use cases for new Data Products built on Data -Mesh, Lakehouse and streaming architecture
- Working experience of up-to-date data & event -driven technologies, such as:
- Testing & Automation: GreatExpectations etc PyTest , Cucumber, Behave, DBT, GCP DVT, Monte Carlo, Soda, Deequ , RestAssured
- Data Engineering & Orchestration: BigQuery , Spanner, Apache Kafka,Airflow, Spark, Cloud Composer, DAGs, Apache Beam, Pub/Sub, Dataflow, DataStage, Teradata, Snowflake, ETL, SQL etc
- Experience of Data Governance & Visualisation tools like: Looker, Ataccama , Dataplex , Collibra, PowerBI




- Strong programming proficiency in one of following coding language - Python (preferable), Java or JavaScript
- Experience of designing & executing complex automation testing strategies and frameworks for Functional and Non -Functional requirements of Data and AI platforms
- Create or accurately request complex test data, referential integrity, data quality and governance taking into account

•I Incorporate automated tests into the CI/CD pipeline and DevOps tooling like Jenkins, Harness, Terraform, Dynatrace etc

- Experience with Agile tools (Jira, Confluence, Xray)
- Experience on Source code management tools (Git, GitHub)

Good to Have:

- AI/ Analytics: Exposure to TensorFlow, PyTorch , Scikit -learn, OpenCV, LangChain and GenAI tools
- DevOps tooling experience like K8, Docker, Terraform, Jenkins, Harness

📌 Data QE (Hyderabad)
🏢 HCL INDIA
📍 Hyderabad