Senior Data Engineer, Data Lakehouse Infrastructure

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Relocation assistance

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Childcare support

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Senior Data Engineer, Data Lakehouse Infrastructure North America | Remote BUILD A SAFER WORLD. TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM's platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. Leading agencies and businesses worldwide rely on TRM to make the world safer and more secure. We're building the foundational data infrastructure powering next-generation analytics at scale. As part of our mission, we're architecting a modern data lakehouse to support complex workloads, real-time data pipelines, and secure data governance-at petabyte scale. We are looking for a Senior Data Engineer to help us design, implement, and scale core components of our lakehouse architecture. You will have ownership over data modeling, ingestion, query performance optimization, and metadata management using cutting-edge tools and frameworks like Apache Spark, Trino, Hudi, Iceberg, and Snowflake. We're looking for engineers with deep expertise in at least one area and a solid understanding of the trade-offs among different technologies. The impact you'll have here: - Architect and scale a high-performance data lakehouse on GCP, leveraging technologies like StarRocks, Apache Iceberg, GCS, BigQuery, Dataproc, and Kafka. - Design, build, and optimize distributed query engines such as Trino, Spark, or Snowflake to support complex analytical workloads. - Implement metadata management in open table formats like Iceberg and data discovery frameworks for governance and observability using Iceberg compatible catalogs. - Develop and orchestrate robust ETL/ELT pipelines using Apache Airflow, Spark, and GCP-native tools

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