Senior Data Engineer, Data Lakehouse Infrastructure
$190k - $220k USD
Build a Safer World.
TRM Labs provides blockchain analytics and AI solutions to help law enforcement and national security agencies, financial institutions, and cryptocurrency businesses detect, investigate, and disrupt crypto-related fraud and financial crime. TRM’s blockchain intelligence and AI platforms include solutions to trace the source and destination of funds, identify illicit activity, build cases, and construct an operating picture of threats. TRM is trusted by leading agencies and businesses worldwide who rely on TRM to enable a safer, more secure world for all.
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 (e.g., Dataflow, Composer).
Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement
What we’re looking for:
5+ years of experience in data or software engineering, with a focus on distributed data systems and cloud-native architectures.
Proven experience building and scaling data platforms on GCP, including storage, compute, orchestration, and monitoring.
Strong command of one or more query engines such as Trino, Presto, Spark, or Snowflake.
Experience with modern table formats like Apache Hudi, Iceberg, or Delta Lake.
Exceptional programming skills in Python, as well as adeptness in SQL or SparkSQL.
Hands-on experience orchestrating workflows with Airflow and building streaming/batch pipelines using GCP-native services.
About the Team:
The Data Platform team is the funnel between all of TRM's data world and product world. We care about all layers of stack including petabyte of data stores, pipelines, and processes.
We have quite a big scope as a the team with new and exciting projects every quarter. As a result, we collaborate across the board with most teams at TRM.
We believe in async communication and are also not afraid to jump on a quick huddle if that helps to move things faster. We are both scrappy when the situation demands and also process-oriented when we need to achieve our OKRs.
We are always looking for people who can elevate the quality our tech and our execution. If you enjoy a remote-first and async friendly environment to achieve efficacy and efficiency at petabyte scale, our team could be a great pick for you!
Team members are based in the US across almost all timezones! Our on-call tends to be in EST/PST shift, whatever suits you the best.
We do try to reserve some overlap in the day for meetings. Our north star - no IC spends more than 3-4 hours/week in meetings.
Learn about TRM Speed in this position:
Build scalable engines to optimize routine scaling and maintenance tasks like create self-serve automation for creating new pgbouncer, scaling disks, scaling/updating of clusters, etc.
Enable tasks to be faster next time and reducing dependency on a single person.
Identify ways to compress timelines using 80/20 principle. For instance, what does it take to be operational in a new environment? Identify the must have and nice to haves that are need to deploy our stack to be fully operation. Focus on must haves first to get us operational and then use future milestones to harden for customer readiness. We think in terms of weeks and not months.
Identify first version, a.k.a., "skateboards" for projects. For instance, build an observability dashboard within a week. Gather feedback from stakeholders after to identify more needs or bells and whistles to add to the dashboard.
About TRM's Engineering Levels:
Engineer: Responsible for helping to define project milestones and executing small decisions independently with the appropriate tradeoffs between simplicity, readability, and performance. Provides mentorship to junior engineers, and enhances operational excellence through tech debt reduction and knowledge sharing.
Senior Engineer: Successfully designs and documents system improvements and features for an OKR/project from the ground up. Consistently delivers efficient and reusable systems, optimizes team throughput with appropriate tradeoffs, mentors team members, and enhances cross-team collaboration through documentation and knowledge sharing.
Staff Engineer: Drives scoping and execution of one or more OKRs/projects that impact multiple teams. Partners with stakeholders to set the team vision and technical roadmaps for one or more products. Is a role model and mentor to the entire engineering organization. Ensures system health and quality with operational reviews, testing strategies, and monitoring rigor.
The following represents the expected range of compensation for this role:
Individual pay is determined by skills, qualifications, experience, and location. The compensation details listed in this posting reflect the US base salary only.
The estimated base salary range for this role is $190,000 - $220,000.
Additionally, this role may be eligible to participate in TRM’s equity plan.
Please note – we factor in the different costs for geographies outside the United States.
Life at TRM
We are building a safer world. That promise shows up in how we work every day.
TRM moves quickly. We are a high velocity, high ownership team that expects clarity, follow-through, and impact. People who thrive here are energized by hard problems, experimentation, and continuous feedback. If something takes months elsewhere, it will ship here in days.
Our work sits at the intersection of AI, national security, and fighting financial crime. The problems are complex, the stakes are real, and the environment evolves quickly. The pace and intensity of the work reflect the importance of the mission. As a result, the way we operate requires a high level of ownership, adaptability, collaboration, and creative problem-solving.
At TRM, you should expect:
Priorities and targets to change quickly as we experiment and iterate
Work that often requires operating with a high degree of ambiguity
A high level of personal ownership and accountability
Close collaboration across teams and functions
Frequent, high-touch communication
Creative problem solving and out-of-the-box thinking
A pace that rewards urgency, adaptability, and outcomes
This environment is energizing for people who enjoy building, solving hard problems, and making progress in situations that are not always fully defined. It also requires comfort navigating ambiguity, adjusting course as new information emerges, and maintaining focus and positivity in a fast-moving and intense environment.
We also recognize that this style of operating is not for everyone. If you are primarily optimizing for predictability or a consistently balanced workload, we encourage you to use the interview process to pressure test whether this environment is truly the right fit. We want teammates who thrive here, not just survive here.
At the same time, many people find this work deeply rewarding. If you are excited by meaningful problems, motivated by ambitious goals, and energized by working alongside mission-driven colleagues, there is a good chance you will find TRM to be an exceptional place to grow and contribute. Learn more: Interviewing at TRM: How We Hire and What Success Looks Like
AI Fluency at TRM
AI fluency is a baseline expectation at TRM.
We believe AI meaningfully changes how top performers operate. We expect every team member to use AI to accelerate and reimagine their craft, not just automate surface tasks.
At TRM, AI fluency means you are among the top 10 percent of operators in your function in how you apply AI to:
Accelerate repeatable workflows
Structure and solve problems
Improve output quality
Increase speed and leverage
You will be evaluated on applied AI fluency during the interview process.
Leadership Principles
We hire and grow against three leadership principles. They’re the standards for how we operate, treat each other, and make decisions.
Impact-Oriented Trailblazer: We put customers first and move with speed, focus, and adaptability. We treat every plan like an experiment – test, ship, measure, and iterate quickly.
Master Craftsperson: We care deeply about our craft. We balance speed with high standards, own outcomes end‑to‑end, and invest in getting better everyday.
Inspiring Colleague: We add clarity and energy, not noise. We bring humility, candor, and a one‑team mindset — giving and receiving feedback to make the team stronger.
Join our Mission
At TRM we care deeply about our craft. We are looking for individuals who want their work to matter, who experiment with speed and rigor, and who take pride in building a safer world for billions of people. If you’re excited by TRM’s mission but don’t check every box, we encourage you to apply — we hire for slope, judgment, and the will to learn fast.
TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore.
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