Senior Data Engineer

As a Senior Data Engineer, you will be an integral part of a cross-functional feature development squad You will play a key role in the evolution of our payments intelligence platform towards a Databricks-native and increasingly agentic operating model. You will design, build and operate secure data ingestion, orchestration and platform capabilities, using Databricks as the first-choice execution platform and Azure services where appropriate. The focus remains on production data engineering rather than AI model development: creating reliable, observable and well-governed foundations that can be operated by both engineers and automated/agentic workflows. You will work across client onboarding, data retrieval, ELT, CI/CD and platform reliability to deliver continuous business value.

JOB ROLEKey accountability of this role:

Delivery, support and continuous improvement of secure, scalable, Azure/Databricks data capabilities and infrastructure on our payments intelligence platform.

Key responsibilities will include:

· Collaborate within a cross-functional squad to define and deliver scalable, secure data and platform capabilities aligned with business outcomes.

· Design Databricks-native solutions as the default, using Spark/SQL, Lakeflow Jobs, Unity Catalog, Volumes and Databricks Asset Bundles, with Azure services used where they add value.

· Build and operate data retrieval and ingestion across APIs, SFTP/FTPS and browser automation, migrating suitable orchestration from external services into Databricks-native workflows.

· Own client data onboarding flows, including configuration, historical backfills, validation, data quality, monitoring and operational handover.

· Build reusable platform capabilities and guardrails that enable agentic workflows to safely automate onboarding, operational diagnosis and routine engineering tasks, with human approval where required.

· Engineer for production reliability through observability, alerting, retries/idempotency, failure recovery, performance and cost optimisation; investigate complex failures and drive root-cause fixes.

· Deliver changes through version control, automated testing, CI/CD and Infrastructure as Code, maintaining secure coding and deployment standards through code review.

· Apply strong security and governance practices across Unity Catalog, Entra/RBAC, secrets, credentials and data access.

· Use advanced Python with strong SQL/Spark skills to develop maintainable, reusable libraries, frameworks and data pipelines.

· Mentor data engineers and drive continuous improvement, evaluating new Databricks and automation capabilities against clear technical and business value.

· 3+ years professional experience as a Data Engineer, DevOps Engineer or Systems Engineer delivering production data platforms.

· Strong hands-on experience with Azure Databricks, including Spark/SQL, workflow orchestration and production lakehouse data engineering.

· Advanced proficiency in Python for data retrieval, processing, automation, integration and reusable engineering libraries.

· Experience designing and operating ETL/ELT pipelines with data quality controls, schema handling, monitoring and failure recovery.

· Expertise in CI/CD, version-controlled deployment and automated testing for data or platform workloads.

· Experience integrating data through APIs and secure file transfer (SFTP/FTPS), including secure handling of credentials and secrets.

· Strong Microsoft Azure knowledge, including ADLS, Azure DevOps and Entra/RBAC, with experience designing and deploying infrastructure.

· Strong production troubleshooting, problem-solving and operational support skills.

· Degree in Computer Science, Mathematics, Physics or other STEM related subject.

What we offer…

• Excellent performance-based earning opportunity, including Objective-driven bonuses.