TRM Labs
Senior Data Engineer, Data Platform
š° USD 190,000 - 220,000/yr
Job Description
[AI-summarized by JobStash]
You will build highly reliable data services that integrate with dozens of blockchains, develop complex ETL pipelines to transform and process petabytes of structured and unstructured data in real time, and design data models for optimal storage and sub-second query latency. You will oversee deployment and monitoring of large database clusters with a focus on performance and high availability, and collaborate with data scientists, backend engineers, and product managers to implement data models that support product needs. You will also create scalable automation for operational tasks, build observability and monitoring solutions, and prioritize fast, pragmatic iterations to deliver production value quickly.
Requirements
- āBachelor's degree or equivalent in Computer Science or a related field
- ā5+ years of experience architecting distributed system architecture
- āStrong programming skills in Python
- āProficiency in SQL or SparkSQL
- āExperience with data stores such as Iceberg, Trino, BigQuery, StarRocks, and Citus
- āFamiliarity with pipeline and workflow orchestration tools like Airflow and DBT
- āExperience with data processing and streaming technologies such as Spark, Kafka, and Flink
- āExperience deploying and monitoring infrastructure with Docker, Terraform, Kubernetes, and Datadog
- āProven ability to load, query, and transform very large datasets
- āAI fluency in applying AI to accelerate workflows and improve output
Responsibilities
- āBuild highly reliable data services to integrate with multiple blockchains
- āDevelop complex ETL pipelines that process petabytes of data in real time
- āDesign and architect data models for optimal storage and retrieval
- āDeploy and monitor large database clusters with a focus on performance and high availability
- āCollaborate with data scientists, backend engineers, and product managers on data model design
- āCreate self-serve automation for routine scaling and maintenance tasks
- āBuild observability dashboards and monitoring to support operations
- āPrioritize pragmatic, fast iterations to deliver operationally usable first versions
Benefits & Perks
- āRemote work (remote-first)
- āEquity plan eligibility