BUILD / SCALE / TRUST

I make production
data systems faster,
simpler, and easier
to trust.

From messy data to reliable products, I build production data platforms with measurable business impact.

Portrait of Onkar Rane
RAW DATABUILD PROCESS DELIVERREAL OUTCOMES

02 License savings

$75Kannual savings

Snowflake submissions replaced paid provider licenses, saving about $75K annually.

03 Performance

30%faster processing

Query and pipeline tuning made S&P Capital IQ processing 30% faster.

04 Automation

15-minutepayment automation

Python, Lambda, and SQS now import payments every 15 minutes.

Experience

TURNING DATA
INTO PROGRESS

A track record of building and operating data systems at scale, in business-critical environments.

Aug 2021 — Present
Singapore & USA

Data Engineer
Partners Group

Build and own production data platforms and business-critical products, lead engineering work, and partner across teams from architecture through operations.

Production work,
measured in outcomes.

I build data products and cloud systems from the data model through production operations, with measurable outcomes for analysts and business teams.

Partners Group

Data Engineer

Aug 2021 — Present

Singapore & USA

Product ownership · Technical leadership

Data platform

Replaced paid data submissions with a Snowflake platform.

Built an API intake and dbt medallion pipeline with Airflow (MWAA) data quality checks. The platform saves about $75,000 in annual licensing costs; I also steward its Collibra catalog.

Snowflake · dbt · Airflow · Collibra
Analytics

Brought 8 TB of music streaming data into investment analysis.

Led two engineers in the Luminate data onboarding, shaping its Snowflake architecture and model alongside Cortex Agents and an MCP layer. Analyst effort fell by more than 50%.

Snowflake · Data modeling · Cortex Agents · MCP
In design

Modeled uneven ownership for a €300M fund commitment.

Partnered with business teams on excuse rights data models and allocation logic for the Q4 2026 onboarding and future deals.

Investment data · Allocation logic · Stakeholder partnership
Performance

Cut a comparables pipeline's processing time by 30%.

Improved the S&P Capital IQ benchmarking pipeline with denormalization, materialized views, query plan tuning, and incremental loads.

SQL · Query planning · Incremental loads
Cloud migration

Migrated a 3 TB SQL Server database to AWS Aurora.

Moved the on-premises workload and reduced annual licensing and hardware costs by approximately $25,000.

AWS Aurora · SQL Server · Cloud migration
AI products

Made portfolio data easier to use and products faster to ship.

Built a FastMCP server for natural language portfolio data analysis and an AI development harness adopted by 15 engineers across four departments, cutting feature delivery time by over 50%.

FastMCP · AWS AI-DLC · Java · React · Data quality
Automation

Replaced manual workflows with production applications.

Built a NAV oversight application in one month, replacing Excel tracking and saving two FTEs per year. Also automated payment imports with Python, Lambda, and SQS on a 15-minute cadence.

Python · AWS Lambda · SQS · EC2 · RDS
Earlier

Graduate Research Assistant

Colorado State University · Jan 2021 — May 2021

Researched representation of Indigenous peoples in academia with the College of Business, contributing insights to the department's academic framework.

TrustOps
Scam triage pipeline

A current build exploring real-time classification and evaluation, with human review for uncertain or high-risk cases.

01 / ModelFine-tuned Qwen2.5-0.5B with LoRA to classify scam type and risk level, measured against a rules baseline on macro F1 and high-risk recall.

02 / StreamStreams cases through Kafka to a typed FastAPI scoring service, routing invalid or high risk output to human review.

03 / QualityUses reproducible SHA-256 data splits, schema validation, and CI that tests and evaluates every push.

Python · Kafka · Hugging Face · FastAPI · Docker · GitHub Actions

The system behind
the outcomes.

Tools matter when they support a sound engineering decision. These are the areas I use to move from diagnosis to a stable production result.

INGESTMODELOPERATEIMPROVE
Data engineering
Snowflake, dbt, Python, SQL, PySpark, Kafka, Airflow, data modeling, ETL, medallion architecture
Cloud platform
AWS S3, Lambda, SQS, EC2, RDS, Aurora, Redshift, Athena, MWAA, CloudWatch
AI systems
MCP, FastMCP, Cortex Agents, semantic views, FastAPI, LoRA, model evaluation
Delivery
Terraform, Docker, GitHub Actions, Collibra, Java, React, Streamlit, Tableau

Credentials,
open for verification.

Each certificate links to the issuer record. No screenshots, no unverifiable badge wall.

Education

Technical depth with a business systems perspective.

2019 — 2021

Master of Computer Information Systems

Colorado State University · Graduate certificates in Business Intelligence and Application Development

2015 — 2018

Bachelor of Engineering in Information Technology

University of Mumbai