Quantitative Data Engineer
US$200,000 – US$220,000 / yr base salary
Posted 20 Jan 2026
Advertised as “Senior Quantitative Data Engineer”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 7+ yrs
- Management level
- People management
| Base salary | US$200,000 – US$220,000 / yr |
|---|
The Role
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.
What you’ll do
- 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 you’ll bring
**What you need:
- 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
- Experience building AI/ML feature stores or RAG 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
We’d love if you had:
- 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
- Skill with performance profiling tools