Senior Data Engineer

Radley James; Amsterdam; On-site; EUR 65,000 - 85,000; Full time

Job summary

A leading quantitative trading firm is looking for an Enterprise Data Engineer to design, build, and scale a next-generation data platform. You will implement data pipelines, collaborate with quantitative researchers, and manage data quality across the enterprise. This full-time role is based in Amsterdam and requires strong experience in data engineering within financial services.

Qualifications

• Strong experience in data engineering within financial services, trading, or high-throughput environments.
• Deep understanding of data modeling, pipeline orchestration, and distributed data systems.
• Hands-on experience with Databricks or equivalent lakehouse platforms.

Responsibilities

• Design and implement robust data pipelines and ETL/ELT workflows.
• Collaborate with researchers, traders, and engineers for high-performance analytics.
• Champion data quality, lineage, observability, and governance.

Skills

Data engineering experience in financial services

Data modeling knowledge

SQL and dbt skills

Experience with Databricks

Understanding of data governance

Real-time data experience

Excellent communication skills

Ownership-driven mindset

Job description

A leading quantitative trading firm combining-edge technology, data, and research to trade global markets is looking for an Enterprise Data Engineer to help design, build, and scale the next-generation data platform.

What You’ll Do

• Design and implement robust data pipelines and ETL/ELT workflows to process large-scale market, reference, and alternative datasets.
• Partner with quantitative researchers, traders, and software engineers to support high-performance analytics and real-time trading systems.
• Champion data quality, lineage, observability, and governance across the enterprise.
• Optimize infrastructure for scalability, resilience, and low-latency data access.
• Contribute to the evolution of our cloud and on-premise data architectures (e.g., streaming, lakehouse, real-time event pipelines).

What We’re Looking For

• Strong experience in data engineering within financial services, trading, or other high-throughput environments.
• Deep understanding of data modeling, pipeline orchestration, and distributed data systems.
• Advanced SQL and dbt skills
• Hands‑on experience with Databricks or equivalent Lakehouse platforms.
• Understanding of data governance and quality frameworks.
• Experience working with real-time data and event-driven architectures.
• Excellent communication and collaboration skills — able to work closely with technical and non‑technical stakeholders.
• A proactive, ownership-driven mindset and a passion for solving complex data problems.

Seniority level

• Not Applicable

Employment type

• Full‑time

Job function

• Finance
• Capital Markets, Financial Services, and Investment Management

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