Job Description This role is a highly technical Data Quality Engineer supporting enterprise data validation and quality engineer efforts across the Azure/Databricks platform. As a senior level developer, this role requires expertise in data testing, automation, distributed systems, and modern data architectures. Other key responsibilities include: - Design and implement end-to-end data validation strategies for pipelines built on Azure Data Factory, Databricks (Delta Lake), and ADLS - Build and perform large-scale data validation using Python and Spark-based validation frameworks - Validate data movement, orchestration workflows, and failure handling - Define and implement data quality SLAs and KPIs along with tracking data/pipeline health Drive best practices for data quality and testing standards We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status,



or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements - 4-6 years' experience in data quality engineer, SDET, data engineering testing, etc. - Solid hands-on experience with Azure Data Factory, Databricks (PySpark), and SQL for data quality validation - Proven experience building automated data quality frameworks from scratch - Strong understanding of data governance, lineage, and metadata Experience integrating with enterprise systems (ERP, CRM, MDM, etc.) - Data observability platforms (Monte Carlo, Soda, Datadog) - Experience building CI/CD data testing pipelines (Azure DevOps / GitHub Actions) - Streaming Technologies (Kafka, Event Hub) - Hands-on experience with dbt (Data Built Tool) - Azure Data Engineer (DP-203) Certification or Databricks Certified Professional Experience within supply chain or large enterprise data environments

📌 Junior Data Quality Engineer - INTL - India (Bengaluru)
🏢 Insight Global
📍 Bengaluru