Senior Quantitative Data Platform Engineer

Millennium; Dublin; On-site; EUR 120,000 - 180,000; Full time

Job summary

Millennium, a global investment firm, is seeking a senior data platform engineer to own and extend its research data platform. You will work on petabyte-scale datasets, optimize storage and compute performance, and collaborate with trading, research, and engineering teams in Dublin and across locations.

Responsibilities include building robust storage layers with Arrow/Parquet/Delta Lake, ensuring high throughput, low latency, and strong production quality through CI/CD and testing.

Qualifications

• 6+ years of kdb+ and systems engineering in a quantitative finance setting.
• Bachelor’s degree in CS, math, physics, or financial engineering.
• Strong kdb+/q skills for platform development and data formats knowledge.
• Proficient with Git, Unix/Linux, Bash and CI/CD practices.
• Ability to optimize correctness, latency, throughput, and cost.
• Experience collaborating across cross-functional teams.

Responsibilities

• Own and extend the internal data platform that stores petabytes of research and production data
• Develop and enhance core storage capabilities with Arrow-backed formats and replication across AWS and on‑prem
• Drive throughput and latency improvements across read and write paths
• Design for concurrency in the distributed compute layer with thousands of readers
• Write, test, document, and maintain code with CI/CD and testing
• Partner with team members on platform direction and architecture
• Collaborate with compute and research teams to meet evolving needs

Skills

kdb+/q

Systems engineering

Distributed storage

C++

Git / Unix / Linux

CI/CD practices

Education

Bachelor’s degree in Computer Science, Mathematics, Physics, Financial Engineering, or related field

Tools

Arrow

Parquet

Delta Lake

S3

PyKX

Database internals

Job description

Millennium, a global investment firm, is seeking a senior data platform engineer to own and extend its research data platform. You will work on petabyte-scale datasets, optimize storage and compute performance, and collaborate with trading, research, and engineering teams in Dublin and across locations.

Responsibilities include building robust storage layers with Arrow/Parquet/Delta Lake, ensuring high throughput, low latency, and strong production quality through CI/CD and testing.