Résumé
Data & AI Engineer
I build the pipelines, data stores, and services behind analytics and AI products.
Credentials

NVIDIA-Certified Professional
Agentic AI
Issued October 2026 · Valid through October 2028
Agent architecture · Evaluation & tuning · Human oversight
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Databricks Academy Accreditation
Lakehouse Fundamentals
Issued July 2021
Delta Lake · Databricks SQL · Security
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WorldQuant University · Applied Data Science II (with honors)
Machine Learning & Statistical Analysis
Issued September 2021
Model tuning · Natural language processing · Time series
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WorldQuant University · Applied Data Science I (with honors)
Scientific Computing & Python
Issued June 2021
Python · Pandas · Data analysis
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Experience
Senior Data Engineer at Quantiphi Inc.
Data infrastructure for healthcare retrieval and AI workflows.
- Building the data foundation for a healthcare RAG platform. Bringing clinical, operational, and knowledge content into Cloud Storage and BigQuery, with lineage, access controls, and vector indexes for retrieval.
- Developing multi-step agents with LangGraph, FastAPI, Vertex AI, and Cloud Run. Adding tool calling, memory, audit logs, and human approvals so teams can review what the agents do.
- Python
- Cloud Storage
- BigQuery
- Dataflow
- Vertex AI
- LangGraph
- FastAPI
- Cloud Run
Data Engineer at Wells Fargo · via Capgemini America
Cloud data engineering for regulated email records.
- 65% improvement in data freshness
- 43 email governance guardrails
- 20 teams with on-demand access
- Moved on-premises batch email governance to Google Cloud, giving 20 downstream teams on-demand access.
- Connected Pub/Sub and Dataflow with Airflow and Cloud Functions for near-real-time email ingestion. Tuned autoscaling, batching, and message acknowledgments, improving data freshness by 65%.
- Added 43 guardrails for PII, legal, finance, and cybersecurity requirements using redaction, exclusion, and audit tagging.
- Helped build a layered lakehouse with BigQuery, Spark, and Apache Iceberg, serving 14 teams across three domains and refreshing 20+ views hourly.
- Stabilized Spark loads across 10 workstreams by fixing skew, memory pressure, shuffle spills, and schema drift.
- Pub/Sub
- Dataflow
- Airflow
- Cloud Functions
- BigQuery
- Spark
- Apache Iceberg
Data Specialist at University of Maryland
Data pipelines and retrieval tools for academic operations.
- 20M+/day live learning-platform events
- 12+ departments using a shared data source
- 100K+ survey responses in a retrieval prototype
- Streamed 20M+ live learning-platform events daily into BigQuery, creating a shared data source for 12+ departments.
- Replaced weekly snapshots with hourly incremental loads using Parquet, Amazon S3, and Redshift, reducing data latency from days to hours.
- Built a retrieval-augmented generation (RAG) prototype over 100K+ survey responses. Used semantic chunking, retrieval, and knowledge graphs to surface themes and quotes, reducing manual review.
- Google Cloud
- BigQuery
- Parquet
- Amazon S3
- Redshift
Senior Software Engineer — Data Engineering at Tiger Analytics
Self-serve data infrastructure for enterprise clients.
- 6 enterprise clients
- 30+ data quality rules
- 4 days → hours data onboarding turnaround
- Worked with a senior architect from design through rollout on a cloud data platform adopted by six enterprise clients over two years.
- Built containerized FastAPI services behind a self-service interface, using Elastic Load Balancing and API Gateway to connect ingestion, source configuration, and asset monitoring.
- Built a data quality engine with Scala, Spark, and Deequ. Added 30+ business rules and dashboards that made anomalies easier to find and investigate.
- Built an Apache Iceberg lakehouse on S3 with AWS Glue. Used partition pruning, compaction, and type 2 slowly changing dimensions for Athena queries and QuickSight reporting.
- Built metadata-driven ingestion with PostgreSQL, Airbyte, Airflow, and Spark, cutting data onboarding from four days to hours.
- FastAPI
- AWS
- Scala
- Spark
- Deequ
- Apache Iceberg
- PostgreSQL
- Airbyte
- Airflow
Education
Master of Information Management at University of Maryland. College Park
- Graduate assistantship as Data Specialist.
- Coursework: distributed systems, retrieval, applied ML, data governance.
B.E. Information Technology at Panjab University, Chandigarh