HYDERABAD · FULLTIME
Data Quality Engineer (Data QE)
Anblick Solutions
Hyderabad · onsite · Posted 5d ago
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Section · 01
About this role
- Design and execute data quality testing strategies for end-to-end data pipelines.
- Perform ETL/ELT testing, source-to-target validation, data reconciliation, and business rule verification.
- Develop advanced SQL queries and Python scripts for data validation and test automation.
- Validate Databricks workflows, Delta tables, and Bronze, Silver, and Gold data layers.
- Test incremental loads, CDC, schema changes, data integrity, and failure-recovery scenarios.
- Build reusable, configuration-driven data quality automation frameworks.
- Integrate automated tests into CI/CD pipelines and workflow orchestration tools.
- Investigate data discrepancies, perform root cause analysis, and collaborate with data engineering teams.
- Leverage AI-assisted tools to improve test case generation, SQL development, and failure analysis.
- Strong SQL skills, including complex joins, CTEs, window functions, and aggregations.
- Proficiency in Python for data validation, reconciliation, and automation.
- Exposure to PySpark for large-scale data processing and validation.
- Strong understanding of ETL/ELT testing, data warehousing, data modelling, and data profiling.
- Experience with source-to-target validation, business rules, and data integrity checks.
- Knowledge of batch/streaming pipelines and formats such as JSON, CSV, and Parquet.
- Hands-on experience with Databricks notebooks, Spark SQL, jobs, and workflows.
- Knowledge of Delta Lake, schema evolution, and Medallion Architecture.
- Exposure to Snowflake, Unity Catalog, and cloud data platforms is desirable.
- Experience building reusable SQL/Python-based test automation frameworks.
- Knowledge of PyTest or similar testing frameworks.
- Experience with Git, Jenkins, Azure DevOps, or equivalent CI/CD tools.
- Familiarity with Databricks Workflows or Apache Airflow.
- Understanding of Generative AI, LLMs, and AI-assisted testing.
- Exposure to RAG pipeline validation, including document quality, metadata, retrieval relevance, and response accuracy.
- Familiarity with LLM evaluation, AI agents, and responsible AI practices is an advantage.
- Experience with Great Expectations, Soda, or Deequ.
- Knowledge of Kafka, data observability, and anomaly detection.
- Exposure to AWS, Azure, GCP, RAG evaluation tools, and data governance.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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Section · 02
Skills
Section · Company
About Anblick Solutions
Anblick Solutions
454
employees
Addison
US
About
Anblicks, a team of specialists in strategic dUnlock the full potential of your data with Anblicks, a team of strategic data modernization experts. Our tailored services cover seamless data migration, robust re-architecture, and transformative solutions. The "AIM" Framework from Anblicks, encompassing Advise, Implement, and Manage, presents a dynamic methodology that simplifies data management. This approach effectively tailors, launches, and maintains data strategies. Anblicks guides its clients in customizing their data foundation, deploying an insight-driven platform, and provides continuous support with its innovative services. This empowers clients to fully leverage their data assets, securing their future capabilities. The framework promotes data democratization and governance, driving growth and enhancing competitive edges through strategic use of data and AI.
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