Job Description

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.

Vice President Expectations

• To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
• If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
• 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 will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
• Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
• Manage and mitigate risks through assessment, in support of the control and governance agenda.
• Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
• Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
• Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
• Adopt and include the outcomes of extensive research in problem solving processes.
• Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills 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.

Embark on a transformative journey as a Senior Data Engineer at Barclays, where you will design and deliver scalable, secure, and high-performing data solutions that power enterprise analytics, regulatory reporting, and digital innovation.

In this role, you will architect and optimize cloud-based data platforms using technologies such as Snowflake, Amazon Redshift, and AWS. You will design data models aligned with ETL and data integration pipelines, working with tools like Databricks, DBT, and Glue to ensure efficient data ingestion, transformation, and accessibility across the organization.

The ideal candidate brings hands-on expertise in data modeling techniques, including ER modeling, normalization/denormalization, and dimensional modeling (Star/Snowflake schemas), along with proficiency in tools such as erwin Data Modeler, SAP PowerDesigner, or ER/Studio. Advanced SQL skills (DDL and DML) are essential for defining database structures, managing data, and optimizing performance.

Strong analytical thinking, problem-solving ability, and clear communication skills are key to translating complex business requirements into efficient, scalable data solutions. You will collaborate within agile teams alongside data engineers, architects, and business analysts to deliver impactful, business-aligned outcomes.

To be successful as a Senior Data Engineer, you should have:

• Cloud-Based Data Platform Knowledge: Experience with cloud data warehousing solutions (e.g., Snowflake, Amazon Redshift, AWS).
• ETL/Data Integration Familiarity: Understanding of data integration processes and tools (e.g., Databricks, DBT, Glue) to design data models that align with ETL pipelines.
• Data Governance & Security Knowledge: Understanding data management standards, regulatory compliance (GDPR, HIPAA), and security protocols to ensure data privacy and quality within the model.

Other highly valued skills include:

• Expertise in Data Modeling Tools & Techniques: Deep knowledge of Entity-Relationship (ER) modeling, normalization/denormalization, and dimensional modeling (Star/Snowflake schemas). Proficiency in industry-standard tools like erwin Data Modeler, SAP PowerDesigner, or ER/Studio is essential for designing these models.
• Advanced SQL Proficiency: Ability to write complex SQL queries to profile, analyze, and manipulate data within relational database management systems (RDBMS). This includes DDL (Data Definition Language) for defining database structures and DML (Data Manipulation Language) for managing data.
• Analytical & Problem-Solving Skills: The ability to translate complex business requirements into structured, efficient, and scalable data models. This involves identifying relationships between entities, ensuring data integrity, and optimizing database performance through proper indexing and partitioning.
• Excellent verbal and written communication to explain technical data concepts to non-technical stakeholders.

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.

This role is based in Glasgow with a hybrid working model of working a minimum of 2 days per week in the office.