Senior Data Engineer

Schonfeld • New York, NY

11d • $150,000 - $190,000

About The Position

As the driving force behind Schonfeld’s next-generation data platforms, you will architect, operate, and continually refine underlying platform that empowers research, systematic trading, AI and risk analytics. On top of this robust foundation, you’ll build and run high-throughput pipelines spanning ultra-low-latency market-data streams to cost-efficient end-of-day workflows. Partner closely with quants, data scientists, and fellow engineers to achieve sub-minute SLAs, shape firm-wide architecture, and mentor peers. We believe diverse backgrounds and voices spark better ideas and more resilient systems, so you’ll join an inclusive culture where every perspective counts.

Requirements

• 7+ years building production data platforms with Python and SQL
• Deep expertise in big-data architecture: partitioning, sharding, columnar formats
• Hands-on with SingleStore/MemSQL, Spark/Flink/EMR and event buses (Kafka/Kinesis)
• Proven AWS skills plus Terraform / CloudFormation infrastructure-as-code mastery
• Experience delivering data services for AI/ML workloads and feature pipelines
• Performance-tuning Postgres, SingleStore/MemSQL, or KDB for sub-second queries
• Proficient in API design, versioning, and OpenAPI/Swagger documentation
• Comfortable collaborating directly with traders, quants, and data scientists

Nice To Haves

• Market-data domain expertise (tick, options, macro)
• Mastery of Iceberg, Delta Lake, or Hudi on S3
• Hands-on work with real-time analytics engines such as SingleStore/MemSQL
• Experience building AI/ML feature stores or RAG pipelines
• Skill with performance profiling tools
• Contributions to open-source data tooling or technical talks

Responsibilities

• Architect and operate the platform – 24x7 reliability, IaC-driven deployments, tight cost controls
• Build and evolve batch and streaming pipelines that ingest billions of market-data events each day
• Architect high-performance, cost-efficient Lakehouse tables
• Expose curated datasets via robust, versioned APIs consumed by quants and AI agents
• Optimize workflows to meet aggressive SLAs, embedding observability and automated data quality checks end-to-end
• Champion Infrastructure-as-Code with Git-driven CI/CD for every data asset
• Mentor junior engineers and enforce best-in-class coding standards
• Continuously refine processes to keep our data ecosystem resilient and lightning-fast

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees