Senior Data Engineer, Data Platform
Build highly reliable data services integrating with dozens of blockchains, develop real-time ETL pipelines processing petabytes of data, design data models for sub-second query latency, oversee large database clusters, collaborate across engineering and product teams, automate operational tasks, and improve observability and delivery speed.
Responsibilities
- Build highly reliable data services to integrate with multiple blockchains
- Develop complex ETL pipelines that process petabytes of data in real time
- Design and architect data models for optimal storage and retrieval
- Deploy and monitor large database clusters with a focus on performance and high availability
- Collaborate with data scientists, backend engineers, and product managers on data model design
- Create self-serve automation for routine scaling and maintenance tasks
- Build observability dashboards and monitoring to support operations
- Prioritize pragmatic, fast iterations to deliver operationally usable first versions
Requirements
- Bachelor's degree or equivalent in Computer Science or a related field
- 5+ years of experience architecting distributed system architecture
- Strong programming skills in Python
- Proficiency in SQL or SparkSQL
- Experience with data stores such as Iceberg, Trino, BigQuery, StarRocks, and Citus
- Familiarity with pipeline and workflow orchestration tools like Airflow and DBT
- Experience with data processing and streaming technologies such as Spark, Kafka, and Flink
- Experience deploying and monitoring infrastructure with Docker, Terraform, Kubernetes, and Datadog
- Proven ability to load, query, and transform very large datasets
- AI fluency in applying AI to accelerate workflows and improve output
Benefits
- Remote work (remote-first)
- Equity plan eligibility