At a Glance
- Tasks: Design and build data pipelines, ensuring quality and scalability in a dynamic financial environment.
- Company: Prestigious financial services client at the heart of global markets.
- Benefits: Competitive daily rate, impactful work, and a chance to shape data infrastructure.
- Other info: Collaborative team culture with opportunities for professional growth.
- Why this job: Join a pivotal project and leave your mark on a leading organisation's data systems.
- Qualifications: 5+ years in data/software engineering with strong Python and Java skills.
The predicted salary is between 60000 - 80000 £ per year.
City of London | Prestigious Financial Services Client. My client sits at the centre of global markets, processing trillions of dollars in transaction value annually and providing reference prices relied upon by the worldwide financial community. This is a genuinely high-impact contract opportunity. You will be joining the Enterprise Data team at a pivotal moment — leading the replacement of a legacy ETL platform (Informatica) with a modern, scalable data engineering architecture. If you are passionate about engineering excellence and want to leave a tangible footprint on a market-leading organisation's data infrastructure, this role is worth a serious look.
What You Will Be Doing:
- Designing, building, and maintaining production-grade data pipelines and infrastructure across data warehouses, with a focus on reliability and scalability.
- Ensuring data quality and integrity across workloads using Python, Java, or Scala, with robust automated validation, monitoring, and testing.
- Developing and managing data lake and data warehouse architectures, including data cleansing, transformation, and governance processes.
- Leading root cause investigations for data incidents and delivering improvements to system stability and performance.
- Evaluating and recommending technical solutions — including prototypes, technical spikes, and proofs of concept — balancing architecture, cost, and business outcome.
- Implementing TDD, CI/CD, and test automation best practices across the engineering team.
- Bridging technical and non-technical stakeholders, communicating clearly on risks, requirements, and project status.
- Collaborating with data scientists and business teams to onboard analytical applications onto robust, monitored infrastructure.
- Contributing to architectural standards. Producing and maintaining high-quality technical documentation and specifications.
Requirements:
- A minimum of five years' experience in data or software engineering, with at least one production-grade data system delivered within financial services or an equivalently regulated environment.
- Strong hands-on Python and Java (Spring Boot) skills; experience across both backend development and data engineering.
- Proficiency with modern data engineering platforms — Apache Airflow, Spark, Kafka, dbt, Snowflake, or similar.
- Solid understanding of data quality principles: pipeline validation, data governance, and compliance.
- Experience with containerisation (Docker, Kubernetes) and CI/CD pipelines.
- Relational database experience: PostgreSQL, SQL Server, or equivalent.
Highly Desirable Skills:
- Cloud platform experience — AWS, Azure, or GCP.
- NoSQL or distributed database experience (e.g. MongoDB).
- Experience designing and operating streaming data pipelines.
- Familiarity with React for light frontend work.
Contract | Inside IR35 | Up to £712/day via Umbrella | City of London
Data Engineer employer: Computappoint
As a leading player in the global financial services sector, our company offers Data Engineers an unparalleled opportunity to make a significant impact on cutting-edge data infrastructure. Located in the heart of the City of London, we foster a collaborative work culture that prioritises engineering excellence and innovation, while providing ample opportunities for professional growth and development. Join us to be part of a prestigious organisation where your contributions will directly influence the future of financial data processing.
