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
Assistant Vice President Expectations
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 us as a Data Engineer - PySpark Developer at Barclays, responsible for supporting the successful delivery of location strategy projects to plan, budget, agreed quality and governance standards. You will be invoved in design, develop, and deliver scalable data solutions. The successful candidate will be responsible for building robust data pipelines, enabling data processing and supporting large-scale data transformation initiatives across the organisation. This role requires strong expertise in PySpark, AWS cloud technologies, data engineering practices and modern data platform architectures. The candidate will collaborate with business stakeholders, architects, product owners and engineering teams to deliver secure, reliable and performant data products.
To be successful as a Data Engineer - PySpark Developer you should have experience with:
Design, develop and maintain scalable data pipelines using PySpark.
Build and optimise ETL/ELT solutions supporting large-scale enterprise data processing requirements.
Develop reusable frameworks, components and standards to accelerate data onboarding and analytics delivery.
Implement data quality controls, validation frameworks and reconciliation processes.
Deliver high-quality code following engineering best practices, coding standards and automated testing approaches.
Some other highly valued skills may include:
Excellent programming skills in Python/Pyspark.
Hands-on experience with Databricks and/or Snowflake.
Strong experience with AWS Cloud services including S3, Glue, EMR, Lambda, EC2, DynamoDB, IAM, CloudWatch and CloudTrail.
Hands-on experience developing and optimising AWS Glue ETL jobs using PySpark.
Experience with large-scale distributed data processing.
Solid understanding of Data Lake, Lakehouse and Modern Data Platform architectures.
Expertise with Git-based source control platforms.
Experience in Airflow.
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.
This role is based out of Bengaluru.

Barclays is a British universal bank. Our vision is to be the UK-centred leader in global finance. We are a diversified bank with comprehensive UK consumer, corporate and wealth and private banking franchises, a leading investment bank and a strong, specialist US consumer bank. Through these five divisions, we are working together for a better financial future for our customers, clients and communities.
With over 325 years of history and expertise in banking, Barclays operates in over 40 countries and employs approximately 83,500 people. Barclays moves, lends, invests and protects money for customers and clients worldwide.
Barclays is a trading name of Barclays Bank PLC and its subsidiaries. Barclays Bank PLC is registered in England and is authorised by the Prudential Regulation Authority and regulated by the Financial Conduct Authority and the Prudential Regulation Authority. Registered in England. Registered No. 1026167. Registered office: 1 Churchill Place, London E14 5HP.