Engineer (India Office)

Data professional with experience in building and validating end-to-end data pipelines across Azure Data Factory, Databricks, and ADLS.

Skilled in data quality assurance, automation using Python and PySpark, and integrating tests into CI/CD workflows.

Adept at large-scale data validation, monitoring data health, and ensuring reliable batch and streaming processes, with additional expertise in developing scalable BI dashboards and reporting solutions.

• Design and implement end-to-end data validation strategies for pipelines built on Azure Data Factory, Databricks (Delta Lake), and ADLS
• Perform source-to-target reconciliation across ingestion, transformation, and consumption layers
• Implement robust checks for Data Quality Dimensions
• Build scalable data testing frameworks using python, pyspark and good knowledge of automation tools like playwright & pyspark based automation testing.
• Integrate automated data tests into CI/CD pipelines (Azure DevOps / GitHub Actions)
• Implement data quality-as-code practices using tools like Soda, dbt etc.
• Validate Spark transformations, Delta Lake tables, and streaming pipelines
• Perform large-scale data validation using PySpark and SQL
• Optimize validation logic for high-volume datasets
• Ensure correctness of: Batch and streaming jobs, Incremental loads (CDC pipelines), Slowly changing dimensions (SCD)
• Validate data movement, orchestration workflows, and failure handling in Azure Data factory & Azure Databricks services
• Define and implement data quality SLAs and KPIs
• Build dashboards to track data health and pipeline reliability
• Proactively identify anomalies and data drifts
• Implement alerting mechanisms for data failures
• Design, develop, and optimize interactive dashboards and reports using BI tools (e.g., Power BI, Tableau, Looker).
• Translate business requirements into technical reporting solutions.
• Identify bottlenecks and improve report/query performance.
• Implement best practices for dashboard design and scalability.
• Establish BI standards, frameworks, and best practices.