Data Engineer

We are looking for a Senior Data Engineer to design, build, and scale the data infrastructure that powers products and decision-making. This role is central to how data flows across the organization-from ingestion and processing to analytics and insights. You’ll work closely with developers, analysts, and trading teams to ensure data is reliable, accessible, and built for the future.

This role combines hands-on engineering with strategic thinking. You’ll contribute to architecture discussions, improve data pipelines, and help shape technical direction. We’re seeking someone who takes ownership, enjoys tackling complex problems, and can deliver impactful solutions across multiple systems and teams., * Design, build, and maintain robust data pipelines for analytics, reporting, and product use cases.

• Contribute to long-term technical roadmap and participate in architecture discussions.
• Build and optimise ETL/ELT processes for small-to-large-scale data processing.
• Develop clear, well-structured data models and maintain documentation to support analytics and self-service.
• Collaborate with software developers, analysts, and trading teams to deliver reliable and scalable data solutions.
• Identify opportunities to improve performance, automate processes, and enhance data quality and reliability.

• Collaborative mindset: Works well with teams, communicates openly, and fosters a positive culture.
• Analytical thinking: Structured, detail-oriented, and curious; focused on accuracy and performance.
• Problem-solving: Able to trace issues across multiple systems and deliver elegant, lasting solutions.
• Communication: Able to explain complex technical concepts clearly to technical and non-technical stakeholders., * Data warehousing: Understand differences between application databases and analytical warehouses; design models for both.
• Python: Strong expertise; C# experience is a plus.
• SQL: Comfortable with complex queries and query tuning on relational and analytical databases (e.g., PostgreSQL, ClickHouse).
• Containers: Experience building, running, and deploying containerised services in local and production environments.
• Cloud platforms: Experience with Azure and distributed systems., * Kubernetes & Helm: Deploying and managing containerised applications at scale with reliability and fault tolerance.
• Kafka (Confluent): Familiarity with event-driven architectures; experience with Flink or KSQL is a plus.
• Airflow: Experience configuring, maintaining, and optimising DAGs.
• Energy or commodity trading: Understanding the data challenges and workflows in this sector.
• Trading domain knowledge: Awareness of real-time decision-making and trading data flows.