Engineering Manager Data Platform

Role Overview

As Engineering Manager for the Data Platform, you will architect the ecosystem powering TrueML’s intelligence and lead a team during a period of intentional scaling. Your focus will be building a reliable, high-performing data foundation that connects raw infrastructure to actionable insights.

Responsibilities

• Lead and grow a data engineering team: manage, mentor, and develop data engineers; foster a culture of technical excellence.
• Architect resilient data infrastructure: design and build data pipelines and systems that can scale company-wide.
• Champion data quality & trust: implement controls and SLAs to ensure production data integrity.
• Collaborate cross-functionally: work with Data Science and Product teams to translate business needs into efficient, well-documented data models.
• Maintain technical excellence: conduct high-impact code reviews and guide optimizations for ETL pipelines and schema performance.
• Stay hands-on when needed: contribute to development and troubleshooting alongside your team.
• Improve data accessibility: make reliable, easy-to-use data available to stakeholders across the company.

Requirements

• Leadership & experience: 2+ years of hands-on management experience and 5+ years of relevant data engineering expertise; experience coaching and growing teams.
• Big data tooling: deep familiarity with Snowflake, Airflow, BigQuery, or Redshift; strong knowledge of both RDBMS and NoSQL.
• Core stack mastery: advanced proficiency in Python or Java and expert SQL, including scaling schemas and tuning ETL performance.
• Data warehouse & workflow systems: experience designing data warehouses and workflow systems, including owning SLAs for critical production processes.
• Communication: able to translate technical challenges into clear, actionable updates for business partners.

Nice-to-Haves / Bonus

• Experience with Spark, Scala, or Protocol Buffers.
• Experience navigating FinTech regulatory challenges.