Designing reliable cloud data systems with a strong focus on
performance, automation, and production-ready delivery across
AWS,
Databricks,
Python,
PySpark, and
SQL.
10+Years in Data Engineering
100+Pipelines Delivered
$20K/moAWS Savings Delivered
Core capabilities backed by measurable outcomes.
Capabilities
Data Pipeline Architecture and Development
Process Automation and Workflow Orchestration
AI/ML Model Integration and Deployment
CI/CD-Driven Deployment and Feature Release
Data Governance and Product Ownership
Performance and Cost Optimization
Team Leadership and Stakeholder Management
BI Reporting and Dashboarding
Project Planning and Agile Ceremonies
Achievements
$20K/month Saved Through AWS Cost and Performance Optimization
15-20 Hours Saved per Run Through Pipeline Redesign
40 hours/month Saved by Automating Validation Workflows
100+ Data Pipelines Built Across AWS, Databricks, Python, PySpark, and SQL
30+ SQL Views and Stored Procedures Migrated from Legacy Platforms to Redshift
Re-Architected Data Pipelines for Scale, Reliability, and Reusability
Owned End-to-End Design, Development, Deployment, and Operations of a Containerized Cloud Map Server
Modeled and prepared FlexPLM application data for analytics,
improving visibility into product lifecycle attributes,
manufacturing workflows, and downstream reporting use cases.
Built ETL workflows for retail sales data to support structured
reporting, sales performance analysis, operational reconciliation,
and business-ready data delivery.