Data Platform Engineering Manager — LATAM

TRM Labs; United States; Hybrid; USD 180,000 - 260,000; Full time

Job summary

TRM Labs is seeking an Engineering Manager, Data to own the platforms powering our intelligence data products—from ingestion and processing to serving and front-end delivery. You will lead two synergistic sub-teams and drive end-to-end outcomes that deliver intelligence to customers faster.

You will guide production systems at scale, mentor a player-coach team, and shape architecture, tooling, and platform investments to raise AI fluency across the org.

Qualifications

• 8+ years hands-on data/engineering experience with 4+ years of direct people management.
• A player-coach who stays close to the technical work—reviewing architecture, debugging pipelines, making system design decisions—while also setting team strategy.
• Must have owned production systems at scale: customer-facing data products, APIs, or decisioning engines – not analytics or BI systems.
• Strong Python and SQL; experience with BigQuery, Airflow, data lake architecture, serving layers.

Responsibilities

• Own the platform that powers TRM’s intelligence data products and support ingestion, processing, and delivery.
• Lead two sub-teams across data infrastructure and product-facing delivery; drive end-to-end outcomes.
• Set the technical direction for production systems and make bets on architecture, tooling, and platform investments.
• Build platforms that accelerate DS teams to test and deliver intelligence data products.
• Hire, mentor, and grow two sub-teams to raise technical quality and AI fluency.

Skills

Data engineering

Leadership

Python

SQL

AI tooling

Production systems

Tools

BigQuery

Airflow

Data lake architecture

APIs

Job description

TRM Labs is seeking an Engineering Manager, Data to own the platforms powering our intelligence data products—from ingestion and processing to serving and front-end delivery. You will lead two synergistic sub-teams and drive end-to-end outcomes that deliver intelligence to customers faster.

You will guide production systems at scale, mentor a player-coach team, and shape architecture, tooling, and platform investments to raise AI fluency across the org.