Senior Data Engineer, Scalable Blockchain Analytics

Trm-Labs; California (MO); On-site; USD 190,000 - 220,000; Full time

Job summary

TRM Labs is seeking a Senior Data Engineer to design and build mission-critical data services that power blockchain analytics at scale. You will architect data models, develop pipelines, and collaborate with data scientists, engineers, and product managers to drive data-driven insights.

The role is based in our San Francisco office with a focus on performance, scale, and reliability. You will work across the data stack including Dataflow, Spark, Kafka, Flink, and cloud infrastructure, delivering

Qualifications

• 5+ years of hands-on experience in architecting scalable data platforms and APIs.
• Proficient in Python with strong SQL skills and distributed systems knowledge.
• Experience with BigQuery and Postgres data stores and modern ETL tooling.

Responsibilities

• Design and build mission-critical data services for TRM's products at petabyte scale.
• Architect scalable data models and pipelines with sub-second query latency.
• Collaborate with data scientists, backend engineers, and product managers to implement data solutions.
• Contribute to data processing tech such as Dataflow, Spark, Kafka, and Flink.
• Write clear design docs and communicate tradeoffs to stakeholders.

Skills

Python

SQL

Spark

Distributed systems

Data modeling

BigQuery

Postgres

Airflow

DBT

Docker

Terraform

Kubernetes

Dataflow

Kafka

Flink

Datadog

LLMs

Education

Bachelor's degree in Computer Science or related field

Tools

BigQuery

Postgres

Airflow

DBT

Docker

Terraform

Kubernetes

Dataflow

Kafka

Flink

Job description

TRM Labs is seeking a Senior Data Engineer to design and build mission-critical data services that power blockchain analytics at scale. You will architect data models, develop pipelines, and collaborate with data scientists, engineers, and product managers to drive data-driven insights.

The role is based in our San Francisco office with a focus on performance, scale, and reliability. You will work across the data stack including Dataflow, Spark, Kafka, Flink, and cloud infrastructure, delivering