Senior Analytics Engineer

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. As a Senior Analytics Engineer on our Advanced Analytics team, you will help mature and scale the foundation of our analytics data ecosystem. You’ll play a leading role in shaping best practices in analytics engineering and will be instrumental in driving data architecture, quality, performance, and reliability across the organization. This is a high-impact, senior-level role built for someone who brings a strong background in analytics/data engineering and data science, and who can thrive in ambiguous environments and independently drive critical initiatives that improve how we model, transform, and use data across TRM. Within 6–12 months, your work will have improved the scalability and reliability of our analytics infrastructure and established the gold standard for analytics engineering practices across the team. The impact you will have here: Lead the development and optimization of analytics pipelines and data models that power TRM’s products, investigations, and decision-making — enabling teams across the company and our customers (including former FBI, Secret Service, and Europol agents) to detect and respond to financial crime in the crypto space. Define and implement best practices in analytics engineering (e.g., testing, observability, versioning, documentation), helping to level up the team’s development workflows and data reliability Improve the scalability and maintainability of our analytics data ecosystem, which process large volume of data, through thoughtful architectural decisions and tooling improvements. Partner closely with data scientists, data engineers, product and business teams to deliver production-ready datasets that support models, metrics, and investigative workflows. Establish best-in-class data quality solutions to increase the reliability and accuracy of our data Investigate performance issues, and bring creative, durable solutions to improve long-term reliability, cost and developer experience. Drive adoption of modern data tools and workflows, helping the team evolve toward best-in-class analytics engineering practices. Contribute to team on-call responsibilities that support the health and availability of our analytics and data science infrastructure (on-call is lightweight and shared equitably). What we’re looking for: 8+ years of experience in analytics engineering, data engineering, or data science with a strong focus on building and scaling analytics workflows. Strong experience across the entire Data Engineering lifecycle (from ETLs, Data Model design, infra, Data Quality, architecture etc.) Deep proficiency in SQL and experience developing robust, modular data models using dbt (or equivalent tools) in a production environment. Strong software engineering fundamentals, including experience with Python, CI/CD pipelines, and automated testing. Proficiency in defining robust and scalable data models using best practices. Experience using LLMs as well enabling AI through high quality data infrastructure. Hands-on experience with cloud data warehouses and infrastructure (e.g., Snowflake, BigQuery, Redshift) and data orchestration tools (e.g., Airflow, Dagster, Prefect). Proficiency in developing compelling dashboards using tools like Looker, Tableau, Power BI, Plotly or similar. Excellent communication skills — you can explain complex technical concepts to non-technical audiences and influence key ... (truncated, view full listing at source)