Data Engineering
5+ DBs Ingested
AWS Enterprise Data Lake & ETL
Centralized S3 Data Lake integrating 5+ DBs with automated PySpark pipelines, cutting silos by 40%.
DATA ARCHITECT
2.8 Years Hands-On Experience
Architecting & scaling enterprise AWS data lakes and distributed PySpark pipelines processing 5M+ records daily. Proven record of cutting pipeline runtimes by 35% and accelerating executive decision intelligence.
PADVEKAR
Scroll to explore data pipelines
Scalable Data Lakes
Distributed PySpark
5M+ Records/Day
AWS Cloud ETL
Power BI Dashboards
Automated Orchestration
Scalable Data Lakes
Distributed PySpark
5M+ Records/Day
AWS Cloud ETL
Power BI Dashboards
Automated Orchestration
Verified Track Record
Measured Production Impact.
- 5M+
- Daily records ingested via AWS ETL
- 35%
- Pipeline runtime optimization
- 20+
- Enterprise BI dashboards deployed
- 99.9%
- Pipeline availability & uptime
Architecture & Impact
Data systems are a competitive advantage.
With nearly 3 years of hands-on engineering experience at Metropolis Healthcare and beyond, I design resilient, fault-tolerant data architectures that transform disparate multi-source databases into centralized cloud data lakes and executive decision intelligence.
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01
Engineer for fault tolerance
Pipelines must heal themselves. Automated Step Functions state machines, error retries, and CloudWatch alarms turn unexpected failures into routine automated recovery.
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02
Optimize at the compute layer
Partitioned Parquet lakes, smart Athena indexing, and PySpark distributed transformations reduced daily pipeline execution runtime by 35%.
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03
Pipelines serve decisions
Petabytes of ingestion are useless without operational clarity. Every ETL job is designed backward from the executive dashboard to ensure sub-second decision speed.
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04
Scale with distributed systems
Monolithic scripts break under volume. I design distributed cloud ETL with AWS Glue, Lambda, and Spark to absorb sudden 10x spikes with zero manual intervention.
Technical Stack
Engineered for Big Data & Cloud
Big Data & Distributed ETL
Cloud Infrastructure (AWS)
Languages & Querying
BI & Decision Analytics
Professional Credentials
Licenses & Certifications.
Industry-verified credentials across Relational SQL, BigQuery analytics, business intelligence visualization, and distributed data manipulation.
Feb 2023
SQL for Data Science
University of California, Davis
May 2023
Google BigQuery & PostgreSQL : Big Query for Data Analysis
Start-Tech Academy
Aug 2022
Data Visualisation: Empowering Business with Effective Insights
Tata Technologies
Jul 2022
Data Manipulation in Python: Master Python, Numpy & Pandas
Udemy
Portfolio & Solutions
Featured Projects. Pipelines & Intelligence.
Production AWS data lakes, distributed PySpark pipelines, executive BI dashboards, and deep learning systems engineered for scale and sub-second decision-making. Click any project card to view full technical architecture and details.
Data Engineering
5+ DBs Ingested
Data Engineering
5M+ Records/Day
Metropolis Healthcare Ingestion
High-throughput ingestion processing 5M+ records daily with automated retries and 35% runtime cut.
Dashboard
Power BI / DAX
Personal Finances Intelligence
Multi-source cash flow, savings rate, and portfolio allocation analytics with dynamic forecasting.
Dashboard
Workforce BI
Enterprise HR Attrition Analytics
Workforce retention dashboard mapping attrition drivers across roles, salaries, and satisfaction.
Dashboard
Geospatial KPIs
Road Accident Geospatial & Safety
Multi-year urban traffic collision analytics highlighting peak risk conditions and safety interventions.
Machine Learning
92% Acc @ 25+ FPS
Vision Vehicle Counting System
YOLOv8-based traffic video pipeline with 92% accuracy at 25+ FPS, automating multi-lane counting.
Deep Learning
94% Accuracy
Deep Learning Spam Detection
LSTM & Bi-LSTM NLP neural networks reaching 94% accuracy, cutting false positives by 22%.
Machine Learning
Streamlit App
Stock Price Prediction App
LSTM neural networks and regression forecasting market feeds deployed inside an interactive Streamlit app.
Professional History
Work Experience.
Hands-on engineering experience designing enterprise cloud data lakes, orchestrating distributed ETL workloads, and delivering analytics to senior stakeholders.
Enterprise Production Role
Data Engineer
Mar 2024 – Present
Leading cloud data lake operations and daily automated ETL ingestion across nationwide diagnostic centers, turning massive healthcare feeds into high-fidelity reporting tables and executive decision dashboards.
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Cloud Pipeline Ingestion: Built and scaled automated AWS ETL pipelines (S3, Glue, Lambda, Step Functions) processing 5M+ records daily across 5+ source relational databases, reducing data silos by 40% and cutting manual reporting effort by 40%.
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Compute & Query Optimization: Optimized PySpark distributed transformations and Athena SQL queries, reducing daily pipeline execution runtime by 35% and accelerating operational and financial reporting cycles.
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Decision Intelligence Dashboards: Designed, deployed, and maintained 20+ production Power BI & QuickSight dashboards for 10+ stakeholder groups across executive, operational, and laboratory divisions, reducing decision turnaround time by 25%.
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Reliability & Orchestration: Architected automated workflow orchestration, error retry state machines, and CloudWatch alert integrations via SNS, maintaining 99.9% pipeline uptime and availability.
Core Tech Stack:
Analytics Internship
Data Analytics Intern
Jun 2023 – Aug 2023 • 3 mos
Spearheaded analytical dashboard development and enterprise business intelligence adoption to measure and optimize student learning engagement across multiple digital curricula.
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Performance Dashboards: Developed 8+ interactive Power BI dashboards tracking key student learning metrics and course progress, boosting reporting efficiency by 50%.
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Engagement Analytics: Analyzed multi-grade student engagement datasets across departments to identify friction points and guide content optimization.
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BI Best Practices & Modeling: Introduced Power BI to the analytics team, establishing data modeling standards and authoring reusable DAX measures for recurring KPI calculations.
Core Tech Stack:
Academic Foundations
Education & Degrees.
MCA — AI & Data Science
D.Y. Patil International University, Pune
Specialized in Distributed Big Data Computing, Cloud Architecture, Machine Learning, Deep Learning, and Enterprise Database Systems.
B.Sc. in Information Technology
D.G. Ruparel College (Mumbai University)
Graduated with Distinction. Comprehensive coursework in Relational Database Management (RDBMS & SQL), Data Structures, Computer Networks, and Software Development.