Niraj Jha
AWS Data Engineer | 3x Certified (AWS, GCP, Databricks) | Building High-Scale Data Platforms
- Role
- Data Engineer at Brillio
- Location
- Mumbai, MH, IN
- LinkedIn followers
- 500 followers
About Niraj Jha
I am a Data Engineer with over 3 year experience designing and optimizing cloud-native data pipelines across AWS and GCP. My expertise spans ETL/ELT development, real-time streaming, CI/CD automation, and data governance frameworks, with proven impact in reducing processing times.Skilled in Python, SQL, PySpark, and Databricks, I specialize in scaling Pandas workflows into distributed Data Lakehouse architectures. I have hands-on experience with tools like Apache Spark, Airflow, AWS Glue, GCP Dataflow, and Terraform, enabling me to deliver end-to-end automation and cost-optimized data solutions.Iām passionate about solving complex data challenges, modernizing ingestion frameworks, and exploring new technologies in Data Lakehouse, real-time streaming, and Data Governance. Recognized with multiple awards at Brillio for innovation and excellence, I bring both technical acumen and a strong collaborative mindset to every project.
Experience
Data Engineer
Apr 2024 ā Present Ā· Bengaluru, IN
Driving Data Engineering initiatives for a Global Fortune 500 QSR (Quick Service Restaurant) client, focusing on modernizing their Supply Chain and Risk Management data platforms on AWS.Key Contributions: Performance Tuning: Re-architected the core ETL framework using AWS Glue & S3, implementing bulk COPY commands to eliminate RDS bottlenecks and reduce pipeline runtime by 50%. Event-Driven Architecture: Designed an end-to-end ingestion system using AWS Step Functions, Kinesis, and Lambda to handle high-velocity supply chain data. Data Governance: Designed a Unified Data Model on PostgreSQL with granular Row-Level Security (RLS), ensuring strict data access controls for global dashboards.š¤ GenAI & DevOps: Automated infrastructure deployment for GenAI workloads using AWS CDK (IaC) and GitHub Actions, reducing manual deployment effort by 80%. Big Data Migration: Led the migration of legacy transformation logic to PySpark on Databricks, utilizing Parquet optimization to cut processing time from hours to minutes.Tech Stack: AWS (Glue, Redshift, Lambda, Step Functions, Athena), Databricks, PySpark, PostgreSQL, Terraform/CDK, Docker.
Education
Ramrao Adik Institute of Technology
Bachelor of Engineering - BE, Instrumentation engineering
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