Senior Quantitative Data Engineer

What you'll do

• Build and operate reliable batch and streaming data platforms, pipelines, and Lakehouse tables.
• Deliver curated datasets through versioned APIs and optimize workflows with observability and data-quality checks.
• Champion Infrastructure-as-Code and CI/CD practices, mentor engineers, and improve platform resilience and performance.

What they ask for

• 7+ years building production data platforms with Python and SQL.
• Expertise in big-data architecture, including partitioning, sharding, and columnar formats; hands-on with SingleStore/MemSQL, Spark/Flink/EMR, and Kafka/Kinesis.
• AWS skills and Terraform or CloudFormation Infrastructure-as-Code mastery.
• Experience delivering data services for AI/ML workloads and feature pipelines, building feature stores or RAG pipelines, and tuning databases for sub-second queries.

Nice to have

• Market-data domain expertise; mastery of Iceberg, Delta Lake, or Hudi on S3.
• Performance-profiling skills, open-source data-tooling contributions, or technical talks.

Pay

$200,000 and $220,000 USD base salary

Tools

Python, SQL, SingleStore/MemSQL, Spark, Flink, EMR, Kafka, Kinesis

AI focus

Build data services and feature pipelines for AI/ML workloads, including AI/ML feature stores or RAG pipelines, and expose curated datasets for AI agents.