9 days ago
Base Salary
$190k - $220k/yr
Responsibilities
- Build highly scalable features integrating with dozens of blockchains.
- Design and architect data models optimized for storage, retrieval, and sub-second blockchain-data query latency.
- Build pipelines, data platforms, and ML or BI workflows from scratch.
- Develop data services and distributed systems from ideation through production deployment.
- Process, load, query, and transform extensive datasets using data processing and streaming technologies.
- Collaborate with data scientists, backend engineers, product managers, and customer-facing teams to translate user needs into scalable data solutions.
- Communicate technical decisions and tradeoffs through clear design documentation and cross-functional alignment.
- Deploy and monitor infrastructure in public cloud platforms.
- Mentor engineers or analysts and improve team capabilities.
Requirements
- Bachelor's degree or equivalent in Computer Science or a related field.
- At least 5 years of hands-on experience architecting scalable API development and distributed systems, and guiding projects from ideation through production deployment.
- Exceptional Python programming skills and proficiency in SQL or SparkSQL.
- In-depth experience with BigQuery and Postgres.
- Proficiency with data pipeline and workflow orchestration tools such as Airflow and DBT.
- Expertise in Dataflow, Spark, Kafka, and Flink for data processing and streaming workflows.
- Experience deploying and monitoring infrastructure using Docker, Terraform, Kubernetes, and Datadog.
- Experience building 0–1 systems, including pipelines, data platforms, or ML/BI workflows.
- Ability to design for performance, scale, cost efficiency, and operational quality.
- Strong written and verbal communication skills with technical and non-technical stakeholders.
- Experience mentoring engineers or analysts.
- Experience with LLMs or AI-powered workflows, such as prompt engineering, internal tooling, or semantic search, is a bonus.
Benefits
- The role is based in the San Francisco office and requires working onsite at least three days per week.
- Eligible employees may participate in TRM’s equity plan.
- The company offers a distributed-first culture with hubs in San Francisco, Los Angeles, New York, Washington D.C., London, and Singapore.
- TRM provides an interview process including recruiter, hiring manager, technical, case study, AI skills assessment, leadership principles, and reference stages.
Tech Stack
Apache AirflowApache FlinkApache KafkaApache SparkDatadogdbtDockerGoogle BigQueryKubernetesPostgreSQLPythonSQLTerraform
Categories
Data Engineering
