Senior Backend Engineer - Data Product

July 18

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TRM Labs

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Blockchain • Cybersecurity • Finance

TRM Labs is a company that delivers blockchain intelligence to detect crypto-facilitated crime and ensure compliance and safety worldwide. Their services include forensics, tactical transaction monitoring, wallet screening, and know-your-entity solutions. TRM Labs supports government agencies, financial institutions, and crypto businesses globally by providing blockchain investigations and risk management solutions to combat fraud and financial crime. They are trusted by leading organizations to help prove crypto cases in court and build safer financial systems.

51 - 200 employees

🔒 Cybersecurity

💸 Finance

💰 $70M Series B on 2022-11

📋 Description

• Design and implement scalable, reliable backend services and APIs that serve complex analytics and insights on blockchain activity. • Engineer data-centric microservices that power features across TRM’s intelligence platform, balancing performance, resilience, and modularity. • Own the full lifecycle of backend systems, from design and implementation to deployment, monitoring, and iteration. • Model and manage large-scale blockchain data, ensuring efficient access and rapid query performance across various products. • Collaborate across product, data science, and infrastructure teams to ensure seamless integration between backend systems and customer-facing features. • Drive technical architecture discussions for backend and data services, and mentor junior engineers on backend best practices.

🎯 Requirements

• 5+ years of backend engineering experience, with deep expertise in designing and scaling backend systems for data-rich applications. • Strong Python development skills; bonus if you've worked with Go or other typed backend languages in production. • Experience designing and maintaining robust APIs, including schema design, versioning, and system observability. • Expertise in distributed data systems: You have hands-on experience with technologies like Spark, Kafka, Flink, or Dataflow for large-scale data ingestion and transformation. • Deep familiarity with data stores like BigQuery and Postgres, including performance tuning for large, complex queries. • Production experience with workflow orchestration tools such as Airflow or dbt, and containerized deployment (Docker, Kubernetes). • Understanding of cloud infrastructure (e.g. GCP, AWS), including CI/CD pipelines, Terraform-based deployments, and observability with tools like Datadog or Prometheus. • Demonstrated success building high-impact backend systems that shipped to production and scaled with user or data growth.

🏖️ Benefits

• PTO • Holidays • Parental Leave for full time employees