Enterprise data discipline, applied to startup problems.
I'm Mudit Tripathi — a data platform architect based in Mumbai, working with startups and growth-stage companies globally. Over 7+ years I've designed analytics foundations for a top U.S. investment bank, a global travel & financial services company, and e-commerce platforms — using AWS, dbt, Airflow, dimensional modeling, and Data Vault.
What I do
I design and build scalable data platforms that turn fragmented company data into trusted business products. My work sits at the intersection of business strategy, analytics, and engineering — the goal is always the same: data products that decision-makers actually trust.
Recent work includes building a cloud-native Data Product Factory for a leading investment bank, designing FX analytics and reporting platforms, delivering analytics foundations for 250+ global retail locations, and implementing scalable data quality and observability frameworks.
Most of my experience comes from environments where getting the data wrong has real financial consequences. I bring that same rigor to startups — scaled down to a pace and budget that makes sense before you're ready for a full data team.
What I specialize in
Where this experience comes from
Seven-plus years across financial services, global retail, and e-commerce — from hands-on engineering to platform architecture leadership.
- Architecting a cloud-native Data Product Factory for a leading U.S. investment bank, enabling scalable onboarding of analytics domains across Commercial & Investment Banking functions.
- Designed reusable dimensional models and dbt transformation frameworks to standardize business logic, improve data quality, and accelerate delivery of analytics products.
- Leading architecture, stakeholder alignment, and platform governance across AWS-based data platforms leveraging Glue, Athena, Iceberg, MWAA, and Datadog.
- Architected a global financial analytics platform consolidating budget and sales data from 250+ retail locations, reducing manual reporting effort by 80% and enabling near real-time KPI visibility.
- Established observability, monitoring, and operational standards across enterprise data pipelines using Airflow, CloudWatch, and Datadog.
- Partnered with finance and analytics stakeholders to define KPI frameworks, metric governance, and data contracts.
- Led development of scalable data ingestion and analytics frameworks for public, regulatory, and commercial datasets.
- Designed reusable transformation pipelines using dbt and Airflow, standardizing data models across multiple domains.
- Delivered analytics solutions integrating Amazon, Flipkart, Nykaa, and Unicommerce, enabling unified sales and inventory reporting.
- Designed APIs, database solutions, and system integrations using PHP frameworks, MySQL, and AWS-hosted infrastructure.
Academic background
Continued learning
Working languages
Why I work with startups specifically
Enterprise platforms have big teams and big budgets to recover from bad architecture decisions. Startups don't. The stakes of getting the data foundation right — early, and without over-engineering it — are actually higher for a startup than for a bank. That's the problem I like solving.
Want to work together?
Start with a short conversation about where your data platform is today.