Join us to build the next-gen Advanced Data and Analytics Platform. We are looking for a dedicated and experienced Data Engineer with very good ETL/ELT and Data Warehousing skills, to work in a collaborative and friendly team on exciting automation deliveries, on premise and in cloud.

As a Data Engineer, you’ll be responsible for the build and delivery of the Ops Analytics Platform across a number of hosting platforms building robust, scalable data pipelines. You will be automating the deployment and maintenance of the Advanced Analytics Platform using the latest and greatest technologies and CI/CD tools such as dbt, GitLab etc. You will also deliver self-service capabilities and automations to enable easy adoption of the Ops Advanced Analytics Platform.

Key skills required for this role include:

Proficiency in Python and SQL is critical for data manipulation and building data pipelines

Ability to design and maintain robust ETL/ELT processes

Strong experience in managing and optimizing data warehouses (e.g., Snowflake, Redshift)

Additional skills include:

Expertise in cloud platforms such as AWS, Azure, or GCP for modern data solutions

Hands-on experience with big data frameworks like Apache Spark or Hadoop

Experience with tools for pipeline automation and monitoring (e.g., Airflow, Prometheus)

You may be assessed on 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 role is based out of our office in Glasgow.

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

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