Senior Data Engineer, Attribution Expansion
TRM LabsLATAMPosted 21 February 2026
Tech Stack
Job Description
<div class="content-intro"><h2>Build a Safer World. </h2>
<p>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.</p></div><p><span class="discussion-level-1 discussion-id-2b9c6489-1a2a-8087-aab3-001c980a683e notion-enable-hover" data-token-index="0">TRM Labs is a blockchain in</span>telligence company committed to fighting crime and creating a safer world. By leveraging blockchain data, threat intelligence, and advanced analytics, our products empower governments, financial institutions, and crypto businesses to combat illicit activity and global security threats. At TRM, you'll join a mission-driven, fast-paced team made up of experts in law enforcement, data science, engineering, and financial intelligence, tackling complex global challenges daily. Whether analyzing blockchain data, developing cutting-edge tools, or collaborating with global organizations, you'll have the opportunity to make a meaningful and lasting impact.</p>
<p>At TRM, we’re constantly building the foundations that power best‑in‑class attribution across dozens of blockchains. As a <span class="notion-enable-hover" data-token-index="1">Senior Data Engineer on the Attribution Expansion team</span>, you will design, build, and operate the data infrastructure and services that turn noisy on‑chain activity into reliable attribution signals at scale. You’ll work closely with blockchain experts, data scientists, and software engineers to encode attribution algorithms into robust data models, ship impactful, high‑throughput data pipelines, and ensure TRM’s attribution stays trustworthy and operationally rock‑solid.</p>
<p><strong><span class="notion-enable-hover" data-token-index="0" data-reactroot="">The impact you’ll have here:</span></strong></p>
<ul>
<li>Build and evolve the <strong>Attribution Expansion infrastructure</strong> so other team members can safely ship new algorithms and data pipelines with minimal friction.</li>
<li>Own end‑to‑end <strong>attribution data pipelines</strong> that turn noisy on‑chain data into high‑quality labels and features used across TRM products.</li>
<li>Standardize how algorithms are implemented and modeled in data, making them reusable, testable, and explainable.</li>
<li>Implement robust <strong>monitoring, data quality checks, and SLAs</strong> for attribution systems.</li>
<li>Improve <strong>developer experience</strong> (templates, tooling, CI/CD, configuration) for other team members working on attribution pipelines.</li>
</ul>
<p><strong><span class="notion-enable-hover" data-token-index="0" data-reactroot="">What we’re looking for:</span></strong></p>
<ul>
<li>Write high-quality code in <strong>SQL</strong> and <strong>Python</strong>.</li>
<li>Strong experience with <strong>Airflow</strong>, SQL and working with <strong>very large data sets</strong> in production.</li>
<li>Broad experience across data modeling, distributed processing, data warehousing / lakehouse, and orchestration. Knowledge of data engineering stack (e.g., Spark/Flink/Beam, dbt, BigQuery/Snowflake/ClickHouse, Kubernetes/Terraform/Datadog, etc.).</li>
<li>Demonstrated ownership and adaptability: able to take initiative, navigate ambiguity, structure complex problems, and ruthlessly prioritize the most critical issues.</li>
<li>Strong collaborator and communicator: works effectively across diverse, cross‑functional teams and clearly communicates complex ideas to both technical and non‑technical audiences, driven by TRM’s mission to build a safer fi ... (truncated, view full listing at source)
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