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.

Assistant Vice President Expectations

To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
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 lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
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.

Join us as a "Data Engineering Support" at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.

You may be assessed on the key critical skills relevant for success in role, such as experience with, skills to meet business requirement as well as job-specific skillsets.

To be successful as a “Data Engineering Support", you should have experience with:

Expert-level proficiency in AWS cloud services including S3, Glue, Athena, Lake Formation, and CloudFormation, with hands-on experience designing and operating cloud-native data platforms.
Strong Python programming skills at a senior level, applied to data engineering, pipeline development, and automation.
Solid experience with ETL/ELT frameworks, data transformation patterns, and data quality tooling (e.g., Great Expectations, dbt, or similar).
Working knowledge of Snowflake for data warehousing, query optimisation, and integration within broader data ecosystems.
Experience with Apache Iceberg or similar open table formats for managing large-scale, versioned analytical datasets.

Some other highly valued skills may include:

Experience with Apache Airflow or similar workflow orchestration tools for scheduling and monitoring complex data pipelines.
Familiarity with IAM, permissions management, and data access governance within AWS (Lake Formation policies, resource-based policies, role-based access).
Understanding of data cataloguing and metadata management practices to support discoverability and governance of enterprise datasets.
Experience with Databricks or Starburst for distributed data processing and federated query engines.
Ability and willingness to collaborate with diverse internal teams across technology, data, and business functions to drive adoption and alignment.

This role is based in Pune.