Dhilip Kumar

Azure Data Engineer with hands-on experience building incremental, watermark-based ETL/ELT pipelines using Azure Data Factory, Mapping Data Flows, ADLS Gen2, and Azure SQL Database with a Bronze-Silver-Gold (medallion) architecture. Skilled in data quality validation, deduplication, upsert loading, and event-driven automation. Strong SQL and Python foundation, plus experience at Amazon Prime Video Sports validating production data in Redshift and Athena (99.9% data integrity).

Data Analyst I – Prime Video Sports at Adecco (Client: Amazon Development Center) (2024-04 – 2024-11)

• Maintained 99.9% data integrity by validating 10,000+ weekly production records in Amazon Redshift using CTEs, window functions, and joins.
• Reduced reporting latency by 25% by automating recurring data preparation and reporting workflows with Python and SQL.
• Cut defect rates by 20% through root-cause and trend analysis of data-quality exceptions and operational defects.
• Raised ML dataset quality from 88% to 95% by preparing and validating structured datasets for downstream machine-learning workflows.
• Accelerated root-cause analysis of data anomalies by building ad-hoc extraction and validation workflows on Amazon S3 and Athena.
• Replaced manual Excel reporting by developing Amazon QuickSight dashboards for content-quality and operational KPIs.
• Increased team productivity by 10% by standardizing recurring data-processing procedures through SOP improvements.

M.Tech in Software Engineering (Integrated 5-Year Program) in Software Engineering – VIT University, Chennai, India (2018 – 2023)