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RemoteFull timeEngineering

Analytics Engineering Manager

TalaUS🇺🇸United States

Quick overview

Salary$160k - $200k/yr
SeniorityMid Senior
Employment typeFull Time
Work modeRemote
LocationUS, United States

Job description

About Tala
Tala is the AI-native credit infrastructure that connects global capital to the global majority.  We combine proprietary risk intelligence with an expanding network of capital and distribution partners to power credit access at scale. To date, Tala has distributed more than $9 billion in capital to more than 14 million customers across Africa, Latin America, and Asia, building the definitive contextual dataset on thin-file borrowers in emerging markets. Tala is now converting that foundation into shared infrastructure that partners, capital providers, and ecosystems can build on.
The company has been named to the Fortune Impact 20 list, CNBC’s World’s Top Fintech Companies twice, CNBC Disruptor 50 for five years, and Forbes’ Fintech 50 list for ten years running.
Given the global nature of our team, we operate on a remote-first approach with office hubs in Santa Monica, CA (HQ); Nairobi, Kenya; Mexico City, Mexico; Manila, the Philippines; and Bangalore, India.
Most Talazens join us because they connect with our mission. If you are energized by the impact you can make at Tala, we’d love to hear from you!

The Role

The Analytics Engineering Manager leads the Analytics Engineering team and is the senior technical leader for the horizontal platform initiatives that make Tala's data usable, trusted, and fast to work with across markets. This person has the authority to set priorities, the technical depth to lead the architecture, and the judgment to know when to build and when to delegate.

This is a hands-on management role: part people manager, part senior architect/builder. The person in this seat manages the Analytics Engineering team, oversees the quality and pace of its work, and acts as lead architect on selected platform initiatives, setting architecture and sequencing for work spanning Analytics Engineering and the data infrastructure they depend on. They are also expected to propose and drive changes that help the team deliver faster and more efficiently. When the work calls for it, they build alongside the engineers delivering it — not as additional throughput, but as the senior technical voice shaping how it gets built. Their time is split between leading the team, architecting selected initiatives, and building, and the balance shifts with what is blocking delivery.

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