Senior Software Engineer - Data Platform

March 15

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TRM Labs

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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.

Anti-money laundering • Blockchain analysis • Transaction monitoring • Crypto compliance • Blockchain forensics

51 - 200 employees

🔒 Cybersecurity

💸 Finance

💰 $70M Series B on 2022-11

📋 Description

• Build highly reliable data services to integrate with dozens of blockchains. • Develop complex ETL pipelines that transform and process petabytes of structured and unstructured data in real-time. • Design and architect intricate data models for optimal storage and retrieval to support sub-second latency for querying blockchain data. • Oversee the deployment and monitoring of large database clusters with an unwavering focus on performance and high availability. • Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement novel data models that enhance TRM’s products.

🎯 Requirements

• A 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 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 Icerberg, Trino, BigQuery, and StarRocks, and Citus. • Proficiency in data pipeline and workflow orchestration tools like Airflow, DBT, etc. • Expertise in data processing technologies and streaming workflows including 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.