Flow Traders is looking for a Senior Data Platform Engineer to join the Data Platform team in our Amsterdam office.

We are a leading proprietary trading firm with an entrepreneurial culture. We value sharp, creative engineers and give them the room and the responsibility to make full use of their abilities.

Your mission is to build and run the platform at the centre of the firm: the source of truth for our proprietary research data, the foundation every department builds on, and the context layer our AI agents depend on. You will make it the place where anyone, human or agent, can find trusted data, understand it, and build on it quickly and safely. Working closely with our Quants and research engineers, you will help shape how the firm does systematic trading.

What you will do

Shape our data architecture. Understand the business challenges of traders, researchers and support functions, translate them into technical solutions, and design the architecture of data systems at Flow Traders.
Make the hard design calls. Decide on data modelling, storage formats and processing patterns, weighing performance, cost and maintainability.
Own performance at scale. Take ownership of the distributed systems, storage and processing platforms that power our data-intensive applications. You will push them to perform under real market load, from tuning a slow pipeline to designing monitoring and alerting that catches problems before our traders do.
Build and maintain platform capabilities. Design and maintain the products our users rely on every day: self-provisioned compute, scheduling, transformations and ad-hoc exploration. Treat quants, analysts and other teams as customers of a platform product.
Run what you build. Keep the platform reliable on busy days, continuously improve resource usage and cost, investigate and resolve data issues and pipeline failures, and build operational tooling and runbooks.
Enable governance and context for AI. Build and maintain the tools that make good governance possible across the firm, such as our data catalog, lineage, access control and configurable data quality rules, and promote their adoption.
Co-develop with AI, responsibly. Use coding agents daily to design, write, test and review code, while owning the correctness of everything that ships.
Raise the bar around you. Mentor engineers through code reviews, design discussions and pairing, including how to work effectively and critically with AI tools.

What you need to succeed

Required

8+ years of experience building and operating multiple data platforms in production across different domains, with the ability to reflect on past technical decisions and lessons learned.
Strong understanding of fundamental concepts including storage layouts, query execution, networking and distributed systems behaviour.
Ability to evaluate and communicate trade-offs between latency, cost, consistency, performance and maintainability.
Strong data modelling and data warehousing experience, including analytical engines such as BigQuery or ClickHouse.
Extensive hands-on experience with distributed storage, messaging systems (e.g. Kafka, Pub/Sub), batch and stream processing (e.g. Apache Beam, Spark), and container orchestration (e.g. Kubernetes).
Strong programming skills in Python and/or Java, with high standards for testing and code quality.
Solid cloud experience across storage, databases (e.g. AlloyDB) and data processing, preferably with GCP or AWS.
Experience with open table formats such as Apache Iceberg or Delta Lake.
Experience with infrastructure as code tools such as Terraform and Helm.
Practical experience with data governance, including data ownership, lineage, access control, metadata management and data quality frameworks.
Understanding of how AI systems consume data, including retrieval, semantic layers, tools and agent interfaces, and how to provide reliable data context for AI applications.
Ability to translate complex business requirements into scalable technical solutions and platform capabilities.