otal Years of Experience : 6+ years Relevant years of Experience: 6 year Mandatory Skills for screening (Limit to top 5 and include version): • 6+ years of experience in data engineering, QA, or data quality roles. • Hands-on with SQL, Python, and data validation libraries (e.g., Great Expectations, Deequ, Soda). • Familiar with data lake/data warehouse architectures (e.g., AWS, Databricks). • Experience with ETL/ELT workflows, monitoring tools, and debugging data issues. • Strong understandingof data governance, metadata, and lineage concepts. Good to have (Not Mandatory): • Experience with data contracts and schema enforcement (e.g., Iceberg, Delta, Hudi). • Exposure to data catalog tools (e.g., AWS Glue Data Catalog). • Knowledge of data privacy and compliance (e.g., GDPR, HIPAA). Detailed Job Description : • Develop and maintain data quality frameworks for batch and streaming pipelines. • Implement data profiling, validation, and anomaly detection tools. • Collaborate with data engineers and business analysts to define data quality rules and SLAs. • Build automated data checks (e.g., null checks, referential integrity, threshold alerts). • Maintain a centralized catalog of data issues and drive root cause analysis. • Work with stakeholders to triage and remediate data quality incidents. • Contribute to the development of data observability dashboards. RTH-Y. • Monitor pipeline health, lineage, and freshness across platforms (e.g., AWS Glue, Databricks, etc.) - U2XDVX