Purpose of the role
To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.
Accountabilities
- Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
- Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
- Development of processing and analysis algorithms fit for the intended data complexity and volumes.
- Collaboration with data scientist to build and deploy machine learning models.
Analyst Expectations
- To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
- Requires in-depth technical knowledge and experience in their assigned area of expertise
- Thorough understanding of the underlying principles and concepts within the area of expertise
- They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources.
- If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
- OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate.
- Will have an impact on the work of related teams within the area.
- Partner with other functions and business areas.
- Takes responsibility for end results of a team’s operational processing and activities.
- Escalate breaches of policies / procedure appropriately.
- Take responsibility for embedding new policies/ procedures adopted due to risk mitigation.
- Advise and influence decision making within own area of expertise.
- Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
- Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function.
- Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
- Make evaluative judgements based on the analysis of factual information, paying attention to detail.
- Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents.
- Guide and persuade team members and communicate complex / sensitive information.
- Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Join us at Barclays as a Data Engineer, where you will design, build, and operate high-quality, reusable data products that power critical business outcomes. In this role, you will engineer and manage end-to-end data product lifecycles—from ingestion and transformation to serving - across pipelines the data platform. You will ensure that data products are trusted, well-governed, discoverable, and fit for purpose, with clear ownership, defined SLAs, and embedded controls.
You will be responsible for: * Designing and delivering scalable, production-grade data products aligned to business capabilities and use cases * Embedding data quality, lineage, observability, and metadata standards to support auditability and regulatory compliance * Ensuring timely, secure, and governed access to data through well-defined interfaces and contracts * Collaborating with product owners, architects, and domain teams to align data products to business outcomes and platform strategy * Supporting the evolution of our data product operating model, enabling reuse, interoperability, and consistent delivery across domains
Your work will directly enable reliable, outcome-driven data products, accelerating value delivery within the Product domain, and beyond.
This role is based in Northampton.
Some other highly valued skills may include: * Cost-Aware Engineering & FinOps: Optimize storage and compute for sustainable scale. * Infrastructure-as-Code & DevOps : Skills in Gitlab, automated deployments, and environment provisioning. * Data Visualisation & BI Tools: Ability to support reporting engineers with Tableau or similar tools for end-to-end delivery. * Experience working within Barclays Agile ways of working, contributing to iterative delivery of data products aligned to business capabilities and measurable outcomes. * Agile Tooling: Strong experience using Jira to manage backlog, ensure traceability from business capabilities to data products, and support governed delivery.
You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills.
To be successful as a Data Engineer, you should have experience with: * Cloud Data Engineering Expertise - Ability to design and build scalable, production-grade data products on AWS (Glue, Athena, S3, Databricks), managing batch pipelines and ETL/ELT processes in alignment with defined SLAs, data contracts, and reuse standards. * Programming & Query Languages- proficiency in PySpark and SQL to develop robust transformations, automate data product pipelines, and deliver high-quality, consumable data assets. * Data Pipeline Design & Optimisation— Ability to engineer and optimise end-to-end data product pipelines, ensuring data quality, reliability, lineage, observability, and security are embedded by design to meet regulatory and business requirements..
