Data Engineer

Join Barclays as a Data Engineer and be part of a major data transformation within our Consumer Credit Risk (CCR) function. We're building a brand-new team in Prague to create next-generation data platforms that will replace legacy systems like Teradata, Hadoop, and SAS. You'll work with modern technologies such as AWS (S3, Lambda, Step Functions), dbt Core, Airflow, and Databricks to build powerful, scalable solutions that support the bank's ability to measure and manage credit risk. Your work will help provide clean, reusable data to data scientists and quants, enabling them to model the likelihood of customers defaulting on loans, assess portfolio health, and run stress tests simulating scenarios like economic downturns.

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:

• Solid hands-on experience in data engineering and data management (ETL/ELT, data pipelines, data quality, data modeling).
• Proficient in SQL and at least one programming language (e.g. Python, Java, Scala).
• Understanding of relational databases and data warehousing principles.
• Experience with any cloud platform (AWS, GCP, Azure) or strong willingness to transition into cloud-based data engineering.
• Familiarity with data transformation frameworks or orchestration tools (e.g. dbt, Airflow, Apache Nifi, SSIS, Informatica etc.).
• Solid understanding of version control (Git-based workflows) and basic CI/CD concepts.

Other highly valued skills include:

• Exposure to AWS services (S3, Lambda, SNS, Step Functions, IAM, Glue, Redshift).
• Experience with distributed data processing (Spark, PySpark, Databricks, EMR).
• Familiarity with modern data architecture concepts (Lakehouse, Data Mesh, Streaming).
• Exposure to credit risk, banking risk, or broader financial services domain.
• Understanding of data governance and regulatory considerations within financial services.

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).

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

• Perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement.
• In-depth technical knowledge and experience in your assigned area of expertise.
• Thorough understanding of the underlying principles and concepts within the area of expertise.
• 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.
• Take 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.