Analytics Engineer

About Addi We are a leading financial platform, building the future of payments, shopping, and banking—a world where consumers and merchants can transact effortlessly and grow together. Today, we serve over 3.6 million customers and partner with more than 55,000 merchants, making Addi Colombia’s fastest-growing marketplace. With a state-of-the-art, technology-first approach, we provide banking solutions (deposits, payments, unsecured credit) and commerce services (e-commerce, marketing), bridging the financial gap for millions and redefining how people experience financial freedom. As the country’s leading Buy Now, Pay Later provider, we have secured regulatory approval to operate as a bank, unlocking even greater opportunities for our customers. In the past year, we have also achieved profitability, reinforcing the strength of our business model and our ability to scale sustainably. Our mission has earned the trust of world-class investors, including Andreessen Horowitz, Architect Capital, GIC, Goldman Sachs, Greycroft, Monashees, Notable Capital, Quona Capital, Union Square Ventures, Victory Park Capital, and more, who back our vision for the future. With their support, we are not just growing—we are transforming Latin America’s financial ecosystem and shaping the next generation to shop, pay, and bank in Colombia. But what truly sets us apart is how we build. We are a conscious company, driven by deep experience in scaling technology, services and products, and we live by our values every day.

About the Role

This is where you come in. Below, you’ll find what this role is all about—the impact you’ll drive, the challenges you’ll tackle, and what it takes to thrive at Addi. If you’re ready to be part of something big, keep reading.

What’s the mission you’ll drive

Own Addi’s marketing data platform, the pipelines and integrations that connect our data to Braze, AppsFlyer, GTM, Marketplace and the App, using AI agents as the default way of working, to make marketing data reliable, efficient and self-service, ensuring Marketing, Growth and Marketplace teams can launch campaigns and measure acquisition with data they trust..

What you will do

Understand and document our marketing data platform Get to know how marketing data flows through the company: where it comes from, how it’s processed, and how it reaches the tools our marketing teams use every day, like Braze, AppsFlyer, and Google Tag Manager. You’ll document it clearly so that both people and AI agents can use it, and propose a prioritized roadmap of improvements.

Make our data pipelines reliable Add testing and monitoring to our most important data pipelines so data arrives on time, issues are caught early, and problems are resolved quickly.

Automate with AI agents Design and launch AI agents and automated workflows that take over repetitive data requests, such as building audience segments, checking data quality, and keeping documentation up to date. You’ll make sure they’re adopted by the team and easy for others to operate.

Make the platform efficient Improve the cost and performance of our marketing pipelines by removing unused or duplicated tables and jobs.

Keep our data organized and trusted Maintain a single catalog of marketing data, with clear owners and approval rules, so everything we send to marketing tools comes from official, trusted sources.

What we’re looking for

Proven experience writing and debugging complex SQL without AI

Writes and reads joins at scale, window functions, CTEs and incremental logic with confidence

Can tell when a query result is wrong and explain why

Builds clean, reusable tables and datamarts that are easy to extend, test and document

Track record of building and operating ELT pipelines on a modern data platform

Hands-on with dbt, Airflow or similar, plus Git and code reviews

Has used SQL warehouses, notebooks and scheduled jobs, and understands catalog, schema, table and permissions (advanced Spark tuning not required)

Uses tests, monitoring and alerts by default; comfortable with on-call and fixing issues at the root

Demonstrates ability to automate and integrate with Python

Builds scripts and API integrations that others can run without the author

Experienced in using coding agents daily for real data work

Uses Claude Code, Codex, Cursor or similar, not just autocomplete