Senior Data Engineer

Join us as a Senior Data Engineer at Barclays and play a key role in transforming how we manage and deliver regulatory data. You’ll work on our Credit Bureau reporting systems, extracting, validating, and delivering high-quality data to external bureaus. We’re looking for a skilled PySpark developer with strong SQL expertise and solid experience in data engineering, ideally with knowledge of SAS or Hadoop. While the current focus is on on-premises technologies, you’ll join a team that’s part of Barclays’ wider strategic move towards cloud and automation, giving you the opportunity to grow your expertise as the environment evolves. This is a chance to help shape a Centre of Excellence for Engineering in Prague, collaborating with risk officers, business stakeholders, and fellow engineers in a tech-driven, knowledge-sharing community that values innovation and modern ways of working.

To be successful in this role, you will need the following:

• Proficiency in PySpark development and distributed data processing.
• Strong expertise in SQL and Python, particularly in building and optimising complex ETL pipelines.
• Hands-on experience or solid knowledge of big data technologies, such as Hadoop, Spark, Hive, or similar frameworks.

Some other highly valued skills may include:

• Familiarity with tools such as SAS, Ab Initio, and dbt.
• Understanding of CI/CD pipelines and Agile methodologies.
• Experience with cloud platforms, particularly AWS services (e.g., S3, Lambda, Glue, Redshift) for ETL solutions, or equivalent experience with Azure or Google Cloud Platform (GCP).

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.

The successful candidate will be based in Prague (Gemini Building).

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.

Assistant Vice President Expectations

• Advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/business divisions.
• Lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. Identify new directions for assignments and/or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc.) to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

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.