Note: The job is a remote job and is open to candidates in USA. Fingerprint empowers enterprises to detect and stop online fraud through device intelligence and identification technology. The Engineering Manager will lead the Data Platform and ML Ops team, overseeing data warehouse reliability and the end-to-end machine learning operations lifecycle while mentoring engineers and driving scalable infrastructure and product outcomes.
Responsibilities
- 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
Skills
- 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
- Experience with ML lifecycle tooling — training pipelines, model serving, and production monitoring
- Experience with AWS and cloud-based data and ML infrastructure
- Fingerprint teammates need to be authorized to work from their home location
- Preferred familiarity with technologies: ClickHouse, DataBricks, dbt, Prefect, DataHub; AWS SageMaker; AWS; Snowflake or BigQuery
Benefits
- 100% remote company
- All-remote work arrangement
Company Overview