Senior AWS Data Engineer

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.

Join Barclays as a Senior AWS Data Engineer and play a key role in a major data transformation journey. Based in Prague, you'll be part of a brand-new team building next-generation data platforms that will replace legacy systems like Teradata, Hadoop, and SAS. Working with cutting-edge technologies such as AWS (S3, Lambda, Step Functions), dbt Core, Airflow, and Databricks, you'll focus on the Credit Bureau system, receiving and managing large volumes of bureau data, while ensuring robust data quality, governance, and controls within the AWS environment.

This is a unique opportunity to shape a Centre of Excellence for Engineering in Prague. You'll collaborate closely with risk officers, business stakeholders, and technical experts to deliver impactful, regulatory-compliant solutions. Barclays is heavily investing in cloud and automation, and you'll be part of a tech-driven environment with an active engineering community that values innovation, knowledge sharing, and modern ways of working.

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

• Strong hands-on data engineering experience delivering production-grade solutions.
• Ability to design, implement and optimise complex data pipelines independently.
• Strong SQL and programming (Python preferred); capable of building reusable and scalable code.
• Experience with modern orchestration tools (e.g. Airflow, Step Functions, etc.).
• Hands-on experience on any cloud platform (AWS preferred or equivalent such as Azure Data Factory, GCP Dataflow).
• Ability to proactively analyse existing processes, suggest improvements, and drive technical solutions end-to-end.
• Comfortable engaging with stakeholders, understanding business requirements, and translating them into technical design.

Other highly valued skills include:

• AWS-native stack: S3, Lambda, SNS, Step Functions, Glue, IAM, Redshift.
• Experience with dbt Core for data transformations.
• Exposure to migrating legacy data platforms (Teradata, Hadoop, SAS) into modern cloud architectures.
• Familiarity with Databricks or similar platforms for advanced analytics.
• Understanding of data security, regulatory, and risk management principles in banking.

You may be assessed on the key critical skills relevant for success in the 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).