Engineering Manager, Data Platform & ML Ops

About the Role:

We are looking for an Engineering Manager to join our Data Platform & ML Ops team. In this role, you will lead the team responsible for Fingerprint's data foundation — from our internal data warehouse that powers business intelligence and product analytics, to the full ML Ops lifecycle that turns raw signals into production models. You'll foster a culture of high performance, helping engineers grow while delivering the reliable, scalable infrastructure our identification and smart signals products depend on. We believe that diverse perspectives fuel innovation, and we encourage candidates from all backgrounds and experiences to apply.

Responsibilties:

• Lead and mentor a team of 4-6 engineers spanning data platform and ML operations.
• Own the reliability, scalability, and evolution of Fingerprint's internal data warehouse — the foundation for business analytics and a direct input to our flagship identification and smart signals products.
• Oversee the full ML Ops lifecycle end-to-end: experimentation, training pipelines, model deployment, and production monitoring.
• Provide technical leadership by collaborating with senior engineers, guiding architecture decisions, and reviewing complex technical proposals.
• Work closely with data scientists, product managers, data analysts and engineering leads to translate data and ML investments into measurable product outcomes.
• Coach and support engineer growth, promoting continuous learning across a fast-moving data and ML landscape.
• Define and evolve platform standards, tooling, and best practices across both domains.

Requirements:

• Minimum of 2 years of experience leading data engineering, ML engineering, or platform teams in an agile environment.  Experience leading teams in a startup or high-growth company.
• At least 5 years of professional experience in data engineering, ML engineering, or adjacent software engineering, particularly within SaaS. Hands-on experience in both data infrastructure and ML systems is a must — you don't need to be an expert in both, but you should be technically credible on both sides of the house.
• Strong technical background across data infrastructure and ML systems.
• Experience managing engineers across multiple technical disciplines.
• Proven ability to lead teams shipping high-reliability data products that prioritize quality and user impact.
• Demonstrated success driving change and innovation in fast-paced, scaling environments.
• Preferred familiarity with technologies: ClickHouse, DataBricks, dbt, Prefect, DataHub; AWS SageMaker; AWS; Snowflake or BigQuery.
• Experience with ML lifecycle tooling — training pipelines, model serving, and production monitoring.
• Experience with AWS and cloud-based data and ML infrastructure.

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Compensation & Transparency

At Fingerprint, we believe in pay transparency — it's part of how we operate as a distributed, remote-first team.  Salaries are based on function, level, and geographic location, benchmarked against similar stage growth companies. 

Because this role is open across the United States and can be based anywhere our team members work from, the salary range reflects that geographic breadth: $159k - $215k. 

Some example salaries for specific locations are below:

NYC:  $187k - $215k

Chicago:  $158k - $183k

Final offer amounts are determined by multiple factors, including the successful candidate's location, experience, and expertise, and may vary from the amounts listed above.