- Led a team of 5 building ingestion pipelines processing millions of records daily across multiple source systems
- Designed Hive table schemas and partitioning strategy for efficient analytics querying
- Automated deployments with TeamCity, UDeploy, and Harness/OpenShift, cutting deployment time from hours to minutes
Tech Lead (Big Data) · Jersey City, NJ
Hi, I'm Aniket.
I'm a data engineer with 10+ years building scalable, cloud-native data pipelines end to end — from ingestion to analytics — using Python, Apache Spark, Databricks, SQL, and Hive on AWS and Azure.
About
I lead data engineering efforts building ingestion pipelines that process millions of records daily, designing schemas and partitioning strategies for efficient analytics, and automating deployments across cloud and on-prem environments. I care about translating messy business requirements into reliable, well-tested data infrastructure — and about automating away the manual toil around it.
Experience
- Built Databricks pipelines ingesting data from S3, RDS, and other sources
- Developed Spark Structured Streaming jobs for real-time ingestion from 5 Kafka topics
- Optimized SQL query performance, reducing runtime by up to 80%
- Built a Python log-analyzer tool that automated manual log inspection, cutting triage time by up to 50%
- Automated routine server maintenance with Python scripts
- Integrated SOAP and REST APIs for data exchange with external systems
Education
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