Tech Lead, Staff Software Engineer, Data Product (US)

TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. The Tech Lead, Staff Software Engineer, Data Product will design and build mission-critical, highly scalable data services that analyze blockchain transaction activity at petabyte scale and deliver insights for TRM’s products.

Responsibilities:

• Build highly scalable features that integrate with dozens of blockchains
• Design and architect intricate data models for optimal storage and retrieval to support sub-second latency for querying blockchain data
• Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement novel data models that enhance TRM’s products
• Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement novel data models that enhance TRM’s products
• You’ll work closely with product managers, data scientists, and customer-facing teams to deeply understand user needs and translate them into scalable data solutions.”
• Our best engineers are also exceptional communicators. They write clear design docs, proactively share tradeoffs, and build alignment across disciplines
• Bonus: Experience with LLMs or AI-powered workflows (e.g., prompt engineering, internal tooling, semantic search)

Requirements:

• • Bachelor's degree (or equivalent) in Computer Science or a related field
• • A proven track record, with 5+ years of hands-on experience in architecting scalable API development, distributed system architecture, guiding projects from initial ideation through to successful production deployment
• • Exceptional programming skills in Python, as well as adeptness in SQL or SparkSQL
• • Versatility that spans the entire spectrum of data engineering in one or more of the following areas:
• • In-depth experience with data stores such as BigQuery and Postgres
• • You've owned 0–1 systems: building pipelines, data platforms, or ML/BI workflows from scratch—not just maintaining legacy.”
• • You simplify complexity. You're skilled at writing and communicating technical decisions clearly to both technical and non-technical stakeholders
• • You're cost-conscious: you design for performance, scale, and efficiency
• • You've mentored engineers or analysts and enjoy leveling up those around you
• • Proficiency in data pipeline and workflow orchestration tools like Airflow and DBT
• • Expertise in data processing technologies and streaming workflows including Dataflow, Spark, Kafka, and Flink
• • Competence in deploying and monitoring infrastructure within public cloud platforms, utilizing tools such as Docker, Terraform, Kubernetes, and Datadog
• • Proven ability in loading, querying, and transforming extensive datasets
• • Bonus: Experience with LLMs or AI-powered workflows (e.g., prompt engineering, internal tooling, semantic search)