Abhishek Kharade

I’m an Azure Data Engineer with 2.7 years of experience building and supporting Azure data engineering solutions, with a strong emphasis on data quality, transformation, and delivering analytics-ready datasets.

At Cognizant Technology Solutions, I designed and maintained 15+ Azure Data Factory pipelines to ingest batch, vial-level, and incremental datasets from APIs, on-prem databases (via SHIR), and flat files into ADLS Gen2. I also implemented a Medallion-style data lake architecture (Bronze-Silver-Gold) to organize raw manufacturing data and create curated datasets for downstream analytics and enterprise integrations.

To transform and validate data at scale, I’ve built workflows using Python, SQL, Pandas, and PySpark in Databricks for data cleansing, schema validation, deduplication, and domain-specific calculations such as yield and activity metrics. I’ve processed large batch datasets ranging from 100K to several million records per run and loaded optimized data models into Azure Synapse Analytics for reporting and downstream systems.

I’m proactive about production reliability—monitoring ETL workflows, implementing data quality checks, handling incremental processing, and collaborating with upstream and analytics teams to resolve data issues quickly. I also supported additional ingestion and transformation for sales, inventory, and supply chain datasets through 10+ ADF pipelines and Databricks-based transformation logic, ensuring accurate and dependable delivery.