Sr. Cloud Data Platform Engineer

Barclays; Glasgow; On-site; GBP 70,000 - 90,000; Full time

Job summary

Join a leading company as a Senior Cloud Data Platform Engineer, where your key responsibilities will include building and maintaining systems for data collection, processing, and evaluation. You will be expected to develop data architectures and collaborate with data scientists, while upholding core values of respect, integrity, and excellence, driving innovation in a secure data environment.

Qualifications

• Experience with Cloud platforms (AWS/Azure) and Data Engineering.
• Knowledge of DevSecOps practices.
• Additional skills in Terraform, Python, Java, Snowflake, and Databricks are highly valued.

Responsibilities

• Build and maintain data architectures and pipelines.
• Ensure data accuracy, accessibility, and security.
• Collaborate with data scientists to deploy machine learning models.

Skills

Cloud platforms

Data Engineering

DevSecOps practices

Terraform

Python

Java

AWS Data Engineering

Azure Data Engineering

Snowflake

Databricks

Job description

Join Barclays as a Senior Cloud Data Platform Engineer, where you’ll be responsible for building and maintaining systems that collect, store, process, and evaluate data—such as data pipelines, data warehouses, and data lakes—to ensure all data is accurate, accessible, and secure.

To be successful in this role, you should have experience with:

• Cloud platforms (AWS/Azure)
• Data Engineering (Airflow/DBT, Spark)
• DevSecOps practices

Additional highly valued skills include:

• Terraform
• Python/Java
• AWS/Azure Data Engineering
• Snowflake/Databricks

You may be assessed on key skills relevant for success in this role, such as risk and controls, change and transformation, business acumen, strategic thinking, digital and technology skills, as well as job-specific technical skills.

This role is based in Glasgow.

Purpose of the role

To build and maintain systems that collect, store, process, and analyze data, such as data pipelines, data warehouses, and data lakes, ensuring data accuracy, accessibility, and security.

Accountabilities

• Build and maintain data architectures and pipelines that enable the transfer and processing of durable, complete, and consistent data.
• Design and implement data warehouses and data lakes that manage appropriate data volumes and velocity, adhering to security measures.
• Develop processing and analysis algorithms suitable for the data's complexity and volume.
• Collaborate with data scientists to build and deploy machine learning models.

Vice President Expectations

• Contribute to strategy, drive requirements, and recommend changes. Plan resources, budgets, and policies; manage and maintain policies and processes; deliver continuous improvements; escalate breaches of policies/procedures.
• If managing a team, define roles and responsibilities, plan for future needs, counsel employees on performance, and contribute to pay decisions. Lead specialists to influence department operations, balancing short and long-term goals, ensuring budgets and schedules meet requirements.
• Demonstrate leadership behaviors: Listen and be authentic, Energize and inspire, Align across the enterprise, Develop others.
• For individual contributors, act as a subject matter expert, guide technical direction, lead multi-year assignments, train and coach less experienced staff, and advise on strategic decisions.
• Advise stakeholders, manage risks, demonstrate leadership in risk management and controls, and understand organizational functions to support business goals.
• Collaborate across departments, develop solutions through analytical thinking, incorporate research outcomes, and build trusting relationships with stakeholders.

All colleagues are expected to embody the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, and to demonstrate the Barclays Mindset: Empower, Challenge, and Drive.