Akash Rajpoot

Data Engineer with 4+ years of experience designing and delivering enterprise-scale data pipelines and cloud data platforms across BFSI, Public Sector, and Investment Management domains. Experienced in building scalable ETL/ELT pipelines and distributed data processing solutions using Azure Data Factory, Azure Databricks, PySpark, ADLS Gen2, Delta Lake, and AWS services including S3, Glue, EMR, Redshift, and Lambda. Strong expertise in processing large-scale datasets (GB–TB scale) using Apache Spark and implementing Medallion Architecture (Bronze, Silver, Gold) for modern data lake platforms.

Proven ability to optimize data pipelines, reduce data latency, and improve data processing performance by up to 30%. Proficient in workflow orchestration using Apache Airflow, AutoSys, and Azure Data Factory with monitoring through Splunk and ServiceNow. Experienced in multi-environment deployments, CI/CD pipelines, and delivering reliable cloud data platforms in Agile environments

Senior System Engineer (Data Engineer) at Infosys Limited (2022-01 – Present)

Architected and maintained enterprise-scale cloud data platforms on Azure and AWS, supporting high-volume data pipelines and optimizing distributed data processing workloads.

• Engineered scalable ETL pipelines using Azure Databricks and PySpark processing 10M+ financial records daily with 99.9% data accuracy.
• Automated complex data transformation workflows improving financial reporting efficiency by 25%
• Optimized Apache Spark workloads using partitioning, caching, and broadcast joins reducing compute cost by 30%.
• Resolved 50+ production incidents using Splunk and ServiceNow ensuring 98% SLA compliance for enterprise data platforms.
• Coordinated release deployments with client teams ensuring stable production releases.
• Managed multi-environment deployments across DEV, QA, and PROD environments.

Bachelor of Technology (B.Tech) in Electronics & Instrumentation – Mahatma Jyotiba Phule Rohilkhand University (2019-06)