Software Engineer · Data & AI
Building large-scale data pipelines and lakehouse systems on Azure Databricks. Currently focused on the intersection of data engineering and AI.
3 years building enterprise data systems at UBS and Credit Suisse — Kafka-based streaming, medallion lakehouses on Azure Databricks, metadata catalogs, and data quality platforms. I care about systems that are observable, recoverable, and actually understood by the teams that run them.
| Layer | Tools |
|---|---|
| Languages | Python · SQL · C++ |
| Data Engineering | PySpark · Kafka · Delta Lake · dbt · Airflow |
| Cloud & Infra | Azure Databricks · ADLS · ADF · Docker · GitLab CI/CD |
| Backend | FastAPI · REST APIs · Microservices |
| Concepts | Medallion Architecture · Metadata Catalogs (DCAT/DQV) · Disaster Recovery |
Software Engineer, Data Platforms — UBS, Pune
Nov 2024 – Present
Lakehouse pipelines processing 50M+ records/day across 6 applications and 200+ downstream consumers. Built a Kafka DataMesh notification framework with exactly-once processing, cut critical pipeline latency from 8 hours to 90 minutes, co-designed an enterprise metadata catalog using DCAT/DQV standards, and improved platform DR coverage from 40% to 90%.
Data Engineer (Technology Analyst) — Credit Suisse, Pune
Jul 2023 – Nov 2024
ETL pipelines for analytics and reporting, data modeling, schema design, and APIs serving curated datasets to downstream applications.
LLM-powered prompt evaluation platform with automated scoring and real-time leaderboard. Built and demoed at the UBS internal hackathon — reached semi-finals in both 2023 and 2024 global editions.
More projects coming — currently building in public.
B.E. Information Technology · Army Institute of Technology, Pune · 2023 · CGPA 9.47