Engineering Manager, Data Platform & ML Ops

Overview

Job Description

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.

Required Skills

• - Minimum of 2 years of experience leading data engineering, ML engineering, or platform teams in an agile environment.
• - 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.