About The Position

The Data Platform team collaborates with an experienced group of data scientists, engineers, and product managers to build highly available and scalable data infrastructure for TRM's products and services. As a Senior Software Engineer on the Data Platform team, you will be responsible for executing mission-critical systems and data services that analyze blockchain transaction activity at petabyte scale, and ultimately work to build a safer financial system for billions of people.

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.
  • In-depth experience with data stores such as Iceberg, 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.

Responsibilities

  • 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.
  • Build scalable engines to optimize routine scaling and maintenance tasks like create self-serve automation for creating new pgbouncer, scaling disks, scaling/updating of clusters, etc.
  • Enable tasks to be faster next time and reducing dependency on a single person.
  • Identify ways to compress timelines using 80/20 principle. For instance, what does it take to be operational in a new environment? Identify the must have and nice to haves that are need to deploy our stack to be fully operation. Focus on must haves first to get us operational and then use future milestones to harden for customer readiness. We think in terms of weeks and not months.
  • Identify first version, a.k.a., "skateboards" for projects. For instance, build an observability dashboard within a week. Gather feedback from stakeholders after to identify more needs or bells and whistles to add to the dashboard.
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