Open to Advisory & Fractional PM roles

Builder PM • 18+ Years

Ranju Ramesh

Platforms ↔ Products

I'm a

Product leader at the intersection of data platforms, developer experience, and AI‑powered products. I build platforms that empower developers and products that protect revenue and reduce risk.

View My Work Download Resume

Ecosystem Experience

Snowflake dbt Databricks Fivetran Azure Spark Snowflake dbt Databricks Fivetran Azure Spark

About Me

The Builder's Journey

Refiner of Data Oil

I started as a Data Warehouse engineer at Tesco in 2008, where I learned to build systems at global scale. That foundation shaped everything that came after — understanding both the technical depth and the user's needs.

Through my journey across Thorogood Associates, ABInBev, Spoonshot, Atlan, 5X, and now Lytx, I've consistently bridged the gap between complex data infrastructure and the humans who need to use it.

"Data generates value only when it flows."

What makes me different: I've been on both sides. I understand the engineer's pain AND the user's needs. I don't just manage products — I ship them.

Currently: Staff PM at Lytx, leading Developer Experience, Partner Experience, and Data Products. Building the ecosystem that makes Lytx an "Ecosystem Champion."

2008

Tesco

Data Engineer

2016

Thorogood

BI Consultant

2018

ABInBev

Technical PM

2022

Atlan

Product Manager

2023

Head of Product

2024

Lytx

Staff PM

Selected Work

Products I've Built

From platforms that power data teams to products that protect enterprises

Lytx • 2024-Present

Data Platform, Developer & Partner Experience

Staff Product Manager — 3 Product Areas

Product Areas

First Data PM at Lytx. Own three strategic product areas: Data Platform modernization, Developer & Partner Experience, and the Lytx MCP Server — an AI-native integration layer connecting Lytx's fleet safety intelligence to the broader ecosystem. Built the 3-year roadmap to make Lytx an "Ecosystem Champion."

Data Platform Developer Experience Partner APIs MCP Server Ecosystem Strategy AI Integration

The Situation

Lytx had no Data PM. The developer ecosystem was ad-hoc, partner integrations were handled case-by-case, and the data platform needed modernization. There was no unified strategy for how external developers, partners, or AI systems would interact with Lytx's data and services.

Data Platform Modernization

Leading the evolution of Lytx's data infrastructure — from legacy pipelines to a modern, scalable platform. Defining the data product layer that powers internal analytics, ML models, and external partner data feeds. Driving the migration strategy and establishing data contracts across the organization.

Developer & Partner Experience

Conducted 40+ stakeholder and partner interviews in the first 60 days. Mapped the full ecosystem landscape — existing APIs, partner pain points, internal gaps. Building a unified developer portal, standardized API patterns, and self-serve partner onboarding. Framed the narrative around making Lytx an "Ecosystem Champion" to gain executive buy-in.

Lytx MCP Server

Pioneering an AI-native integration layer using the Model Context Protocol (MCP). The Lytx MCP Server enables AI agents and LLM-powered applications to programmatically access fleet safety data, driver risk scores, and video event insights — turning Lytx's intelligence into a composable building block for the AI ecosystem.

What I Learned

The first PM in a domain doesn't inherit a backlog — they inherit an information vacuum. The job is to create clarity before creating tickets. And when you own multiple product areas, the real leverage is in the connections between them.

5X • 2023-2024

5X Data Platform — Open Source at Scale

Head of Product

Products Shipped

Built the product org from scratch (4 PMs, 3 Designers, 1 Ops) and shipped commercial versions of dbt, Superset, Airflow, and Airbyte with unified authorization. Achieved product-market fit velocity in 8 months.

dbt Superset Airflow Airbyte Product Org Building

The Situation

5X had engineering talent but no product function. Open-source tools (dbt, Superset, Airflow, Airbyte) needed to be packaged into commercial products with unified authorization, but there was no product org, no designers, and no process.

The Approach

Built the product org from zero: hired 4 PMs, 3 Designers, 1 Ops. Defined the product vision around "one platform, one auth" — commercial-grade wrappers around best-in-class open source. Shipped 4 products in 8 months by running parallel squads with shared design systems and unified API contracts.

What I Learned

Building a product org is itself a product problem. You're shipping a team that ships products. Get the hiring sequence right and velocity follows.

Atlan • 2022-2023

Data Discovery & Ecosystem Integration

Product Manager

Integrations in 6mo

Owned integrations and discovery experience. Built dbt Semantic Layer integration showcased at dbt Coalesce 2022. Developed 3 strategic partnerships with major data ecosystem players.

dbt Snowflake Databricks Partner Integrations

ABInBev • 2018-2021

BrewRight — Legal & Compliance Analytics

Technical Product Manager

$200M

Recovered

Award-winning legal and compliance analytics platform for anti-bribery, corruption, and money laundering detection across 50+ countries. Led a 12-person team, built DevOps with CI/CD, and architected ML models for predictive analytics.

Azure Spark Databricks PySpark ML Salesforce Einstein

The Situation

ABInBev — the world's largest brewer — had no centralized system to detect anti-bribery, corruption, or money laundering across 50+ countries. Compliance teams relied on manual audits and disconnected data sources, leaving hundreds of millions in risk exposure undetected.

The Approach

Led a 12-person cross-functional team to build BrewRight from scratch. Architected the platform on Azure + Databricks with Spark pipelines processing global transaction data. Built ML models (PySpark + Salesforce Einstein) for predictive risk scoring. Established DevOps with CI/CD — a first for ABInBev's legal tech. Designed the product to surface actionable compliance insights, not just dashboards.

What I Learned

The best compliance tools don't feel like compliance tools. When you make the right thing the easy thing, adoption follows. BrewRight won internal awards because legal teams actually wanted to use it.

Thorogood Associates • 2016-2018

Enterprise BI & Forecasting

BI & Analytics Consultant

$320M

Supply Chain Savings

Served as Delivery Manager, SME, and Technical Architect for enterprise BI and forecasting solutions. Delivered a forecasting platform that enabled $320M supply chain savings over 3 years for a leading CPG.

BI Forecasting CPG Enterprise Analytics

Tesco Bengaluru • 2008-2015

Grocery Shopping Service — Data Warehouse

Senior Software Engineer

Global

Scale

Designed the Data Warehouse solution supporting Tesco's grocery shopping service, implemented globally. Built E2E systems for master data and transactional systems. This is where I learned to build at scale.

Data Warehouse ETL Master Data Global Scale

What People Say

Voices That Matter

From engineers, executives, and partners I've built with

Ranju has a rare ability to hold the full picture — from data pipeline architecture to executive storytelling — and translate between them without losing fidelity in either direction. He built the product function at 5X from nothing, and the velocity we achieved in those 8 months was a direct result of how he structured the team and the work.

Arpit K.

CTO · 5X Data Platform

What sets Ranju apart is that he actually understands the data stack — not at a buzzword level, but deeply. At Atlan, he owned the integrations roadmap and shipped 10 ecosystem integrations in six months while also driving one of our most high-profile conference moments at dbt Coalesce. He operates like a founder, not a PM.

Shivangi P.

VP Product · Atlan

BrewRight was the first internal product at ABInBev that legal teams actually wanted to use. Ranju understood that the best compliance tool is one that doesn't feel like one — and he built exactly that. The $200M recovery speaks to the impact, but the adoption rate across 50+ countries speaks to the craft.

Marcus R.

Global Legal Technology Lead · ABInBev

How I Can Help

Let's Build Together

Whether you're scaling a data platform, launching a developer ecosystem, or turning data into products

🏗️

Build Your Data Platform

Turn your data infrastructure into a competitive advantage. Define strategy, architect for scale, set up governance, and build data products that deliver measurable business value.

Best for: Companies sitting on valuable data but struggling to unlock it

🔌

Launch Your Ecosystem

Make your platform the center of an ecosystem. Design API and developer experience strategy, build partner integration frameworks, and develop ecosystem roadmaps that attract partners.

Best for: Platform companies wanting to become "ecosystem champions"

🚀

Ship Products Faster

From zero to product-market fit. Stand up a product function, define vision and roadmap, implement product ops, and navigate the 0→1 and 1→10 phases with velocity.

Best for: Startups and scale-ups needing to accelerate delivery

🎯

Bridge Technical & Business

Translate complexity into clarity. Align engineering and business teams, make build vs. buy decisions, evaluate data tools, and coach technical PMs.

Best for: Organizations where tech and business teams struggle to align

$200M

Recovered through BrewRight

Products shipped in 8 months

Person product org built

18+

Years building at scale

How I Think

Product Philosophy

The principles that guide how I build products and lead teams

Data flows, value follows

Data generates value only when it flows. Every platform decision I make is tested against: does this reduce friction in the data supply chain, or add it?

Build for the builder

The best developer tools disappear. I obsess over the experience of the person integrating, deploying, and debugging — not just the end user clicking buttons.

Ecosystems compound

Single products grow linearly. Platforms with ecosystem strategies grow exponentially. I think in terms of API contracts, partner incentives, and network effects.

Ship the org, then the product

Velocity comes from team structure, not individual heroics. I build the product function — hiring, process, culture — before expecting the product to ship itself.

Writing & Insights