Engineering Manager, Data Platform

Job description

Alloy is where you belong!

Alloy is the AI-powered identity and fraud prevention platform that accelerates onboarding, stops fraud, and scales compliance across the customer lifecycle so financial organizations can grow without limits. More than 900 of the world's leading financial institutions and fintechs trust Alloy for smarter risk management that drives growth.

Through our values: Be Bold, Go Fast, Collaborate, and Celebrate Our Differences, we are creating a workplace where you can grow, thrive, and belong. See how we’ve been continuously recognized and named one of Inc. Magazine’s Best Workplaces, Forbes America’s Best Startup Employers, Best Fintech to Work for by American Banker, year after year.

Check out our investors and read more about us here.

About the team

The Data Platform team sits within Alloy's Intelligence vertical and owns the infrastructure that powers how data is modeled, governed, and delivered — both internally and to customers. We work at the intersection of data engineering and analytical depth, with a stack built around dbt, Snowflake, and Artie, and a growing investment in our semantic layer.

This is an early but high-leverage moment for Analytics Engineering at Alloy. We have the tooling, the data, and the leadership experience to build this function the right way — and this role is central to that effort. The person who joins will help establish the patterns, standards, and culture of Analytics Engineering here.

The strategic stakes are real: native warehouse data delivery is becoming a core part of how we serve customers, agentic workflows depend on a well-maintained semantic layer, and OLAP infrastructure is increasingly woven into our product stack. Analytics Engineering sits at the center of all three.

Alloy operates in a hybrid-work environment. We look to foster collaboration and community by having our local employees onsite three days a week.

What you'll do

You'll manage the Data Platform team: hire for it, grow the people on it and set its direction. This is a player-coach role. Roughly half your time goes to hands-on work on the platform, and the other half to leading the team.

• Lead a team of two engineers. Set clear direction, run one-on-ones and performance reviews, give direct feedback and coach each person toward work that stretches them

• Hire as the team grows. Define the roles, run the interview loops and decide who joins

• Own the data platform end to end: ingestion and change data capture, the Snowflake warehouse, dbt and the semantic layer, and the tooling that internal and customer-facing analytics run on

• Ship native warehouse data sharing into customers' own environments, including the schema contracts customers will build on for years

• Design how sensitive customer data is handled across analytics and BI, so teams get the answers they need and customer data stays protected

• Set the team's technical standard for modeling, testing, documentation and code review, and meet it in your own code

• Work with Product, Compliance and other engineering teams to decide what data we expose, to whom and under what constraints. Make the platform good enough that teams choose it over building their own

What we're looking for

You want both halves of this job. You'd be unhappy in a role that took you away from building, and just as unhappy in one where nobody grew because of you.

• Deep analytics engineering and data systems experience. Strong SQL, dbt and a cloud data warehouse (Snowflake preferred), with real depth in data modeling: grain, slowly changing dimensions and what makes a model trustworthy

• Experience owning architecture from ingestion through the warehouse to delivery, including ingestion and change data capture tools (Artie or similar) and how they fail: late-arriving data, schema drift, out-of-order events

• A record of leading people. You've set direction others followed, grown someone on purpose, given feedback that was hard to give and raised a team's standard. Formal management experience is not required. We care about what you did, not the title you held

• Good judgment about sequencing. Given more good ideas than quarters, you pick what comes first and can explain why the rest wait

• Experience getting other teams to adopt something you built, or agreeing a constraint with a function that had reasons to resist, with the relationship intact afterwards

• Based in the New York City area and able to work from our Union Square office Tuesday through Thursday

Nice-to-haves:

• Experience with native warehouse data delivery, such as Snowflake Data Sharing or Marketplace

• Background in fintech, financial services or another regulated industry, especially handling PII in analytics

• Experience building a semantic or metrics layer and connecting it to BI tools

• Exposure to agentic or LLM-based workflows and the data infrastructure behind them

We're a lean team, so your impact will be felt immediately, and opportunities w

Prepare for the interview

Nothing collected for this employer yet. The Blind 75 is what technical screens draw from; practice it here, with a coach, in Java or Python.

More at Alloy

• Sales Manager, Fintech · New York City
• Director of Operations (Product, Engineering & Technical Solutions) · New York City
• Senior Solutions Architect - Transaction Monitoring · Remote
• Senior Solutions Architect - IAM · Remote
• Senior IT Security Engineer · New York City
• Deal Desk Analyst · New York City
• Senior Solutions Engineer · London, UK
• Strategic Partner Development Manager, Banking · New York City

More like this

• Engineering Manager jobs in New York City, NY (4)