Senior Data Engineer - Financial Flows

Description

The company simplifies global trade data and turns it into insights that help clients in commodities, energy and maritime make decisions. Founded in 2014, it has more than 850 staff across 69 countries and builds platforms that turn complex market data into plans clients can act on.

This senior role sits in the Financial Flows team, which builds commodity finance analytics. You will own the pipelines, predictive models and cloud infrastructure end to end, lead the move of production services to AWS, and rebuild legacy calculation engines as clean, fast Python services. The work sits between quantitative research and cloud infrastructure, delivering real-time, critical market insight to participants in global commodities markets.

You are encouraged to apply even if you do not match 100% of the requirements, since experience takes many forms.

Responsibilities

• Build and run resilient batch and streaming ingestion pipelines that pull data from external financial market providers through APIs and WebSockets.
• Lead the move of legacy backend systems to cloud-native AWS, setting firm standards for reliability and scale.
• Refactor the CTA positioning indicator calculations from PHP to Python, matching the mathematical output exactly, with thorough tests and low latency.
• Model complex futures pricing, open interest and trading volume data in time-series stores and search engines such as QuestDB and Elasticsearch.
• Add automated validation, alerting and monitoring so market feeds stay accurate, continuous and fault tolerant.
• Deploy and scale containerised services on Docker and Kubernetes through automated CI/CD pipelines and GitOps workflows.
• Work with quantitative researchers, commodity analysts and product managers to turn trading models into production pipelines that perform well.
• Mentor engineers through code reviews, system design guidance and architecture documentation.

Requirements

• 5+ years of professional experience building, running and scaling production data pipelines and backend infrastructure.
• Expert Python, with a record of refactoring and rewriting critical production code for speed and testability.
• Hands-on experience building real-time or streaming API ingestion (REST, WebSockets) for time-series data.
• Production experience running containerised applications on AWS with Docker, Kubernetes and modern CI/CD practices.
• Solid SQL skills and experience with distributed search or time-series databases such as Elasticsearch, QuestDB or ClickHouse.
• Deep experience building automated data quality frameworks, observability (monitoring and alerting), and root-cause troubleshooting for production systems.
• Nice to have: knowledge of financial market structure, futures contracts, open interest and commodities trading symbology.
• Nice to have: experience integrating data from major financial market vendors such as Bloomberg, LSEG, Enverus or Trading Technologies.
• Nice to have: experience migrating legacy PHP code or reading PHP algorithms to translate them into Python.
• Nice to have: practical familiarity with GitOps frameworks and infrastructure-as-code tooling.

Conditions

The company is an equal opportunity employer that welcomes people of all backgrounds, experiences, abilities and perspectives.