Professional Summary
Data Engineer with over 5 years of experience designing scalable ETL pipelines and analytics solutions on Azure and AWS. Specializes in streamlining data workflows using Spark, Kafka, and Python while maintaining rigorous DevOps standards. Recognized for reducing query latency and improving data reliability across cross-functional teams.
Skills
- Azure
- SQL
- AWS
- ETL
- Python
- Spark
- Ci/Cd
- Communication
- Power Bi
- Scala
- Agile
- Kafka
- Data Modelling
- Microservices
Experience
Data Engineer — Forage AI
- Architected a serverless data platform on Azure that ingests 1.5M daily events and reduced processing latency by 40%.
- Implemented CI/CD pipelines that accelerated analytics feature releases from quarterly to monthly while improving test coverage to 95%.
- Spearheaded migration of legacy ETL workloads to Azure Data Factory and Databricks, lowering compute costs by 30%.
- Designed APIs serving 100K+ monthly active users with real-time inventory and recommendation data.
- Mentored junior engineers on data engineering best practices and Azure service utilization.
ETL Developer — ValueMomentum
- Optimized Oracle data warehouses with partitioning and indexing strategies that improved BI query performance by 60%.
- Led cross-functional workshops to define data product roadmaps and ensured engineering alignment with analytics needs.
- Developed Apache NiFi flows that automated partner data integrations and reduced manual validation hours by 80%.
- Codified data quality checks in the ETL pipeline, catching 95% of upstream discrepancies before they reached reporting.
- Contributed to migration of on-premise workloads to AWS Glue and Redshift, enabling self-service analytics.
Education
B.S. Software Engineering
Ohio State University
Certifications
- Microsoft Certified: Azure Data Engineer Associate
- AWS Certified Solutions Architect – Associate
Languages
English, Telugu