Data Engineer

5 days ago

Singapur, Singapore DYMON ASIA CAPITAL (SINGAPORE) PTE. LTD. Full time

We’re rebuilding our technology and data platform from the ground up—and we’re looking for superstar Data Engineers to help lead the change. If you’re a curious, creative problem solver with 4–10 years of hands-on experience, this is your chance to shape the pipelines that power everything from multi-asset investment strategies to AI-driven insights.

You’ll architect the data backbone that fuels our research, risk systems, and execution workflows. If you thrive in high-performance environments and love turning raw data into reliable, scalable infrastructure, we want to hear from you.

Responsibilities
  • End-to-End Pipelines: Design, build, and optimize scalable data pipelines for structured and unstructured financial datasets.
  • Core Data Delivery: Collaborate with discretionary PMs to deliver timely, trustworthy data for decision-making.
  • Quant-Ready Infrastructure: Partner with systematic teams to shape data for advanced analytics and modelling.
  • API Innovation: Help evolve our data delivery platform with user-friendly APIs accessible via Excel, Python, and more.
  • Quality at Scale: Implement monitoring, validation, and remediation frameworks to ensure data accuracy and consistency.
  • Governance Advocacy: Champion standards, lineage, metadata, and security across the data ecosystem.
  • Automation & Efficiency: Drive ETL/ELT automation using cloud-native and distributed systems.
  • Vendor Integration: Work with internal and external data providers to onboard and manage critical data assets.
Qualifications
  • A Bachelor’s or Master’s in Computer Science, Engineering, or a related field.
  • Strong coding skills in Python and SQL, plus experience with distributed systems like Spark, Kafka, or Hadoop.
  • Deep knowledge of lakehouse architectures and open table formats (Iceberg, Delta Lake, Parquet).
  • Hands-on experience with cloud platforms (Azure preferred) and modern data warehouses (Databricks, Snowflake, Redshift).
  • A proven track record of building resilient data infrastructure in high-performance or financial environments following CI/CD.
  • Familiarity with financial data nuances—traditional vs alternative, structured vs unstructured, batch vs real-time—and a sharp eye for point-in-time modelling.
  • A detail-oriented mindset, ownership mentality, and strong communication skills in fast-paced, collaborative settings.
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