Data Engineer, Elliptic

• Enjoy writing clean, well‑tested, and efficient code
• Use data and experimentation to make informed decisions
• Thrive in a collaborative, open culture where sharing and feedback are part of daily work
• Are curious about new technologies, particularly how AI and automation can optimise data engineering
• Appreciate an environment that values autonomy, mentoring and personal development
• Several years of experience (typically around 3–5 years) in data engineering or big data systems
• Experience delivering and maintaining distributed data pipelines
• Practical knowledge of Spark, Databricks, or similar big data frameworks
• Familiarity with cloud infrastructure (AWS, Azure, or GCP)
• Understanding of data architecture trade‑offs such as scalability, resilience, and observability
• Interest or experience in functional programming
• Don’t tick all the boxes? We’re still interested to hear from you if you think you’d be a good fit

Desirable

• At Elliptic, we’re building the intelligence layer for the future of finance. Our Data Fabric team turns complex blockchain data into actionable insight, empowering financial institutions, regulators, and businesses to innovate with confidence. Guided by our mission to make digital‑asset intelligence seamlessly accessible, the team builds and scales the unified data platform that powers Elliptic’s analytics and decisioning products
• As a Data Engineer, you’ll design and optimise systems that process large‑scale blockchain and off‑chain datasets, enabling organisations worldwide to make trusted, data‑driven decisions
• You’ll work on challenges spanning batch and streaming data, building blockchain‑agnostic solutions and solving complex data‑processing problems that reveal how value moves through the crypto ecosystem
• Build and maintain distributed data pipelines using Scala, Spark, and cloud technologies
• Collaborate with engineers, data scientists, and product teams to deliver reliable, scalable data systems
• Design and optimise data ingestion and transformation workflows for blockchain and off‑chain datasets
• Ensure accuracy, scalability, and efficiency in systems processing hundreds of millions of daily data points
• Evaluate design options and trade‑offs across scalability, performance, reliability, and cost
• Contribute to the full lifecycle of data platform development, design, deployment, and continuous improvement
• Strengthen pipeline reliability, observability, and automation through code and tooling improvements
• Grow your influence and take on greater responsibility as you deepen your understanding of our distributed systems
• Tech environment:
• Scala | Spark | Databricks | AWS | Airflow | Kubernetes | Terraform | Functional Programming
• (No Scala experience yet? If you are an experienced data engineer eager to learn, we will support you.)