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Date live:
Apr. 10, 2026
Business Area:
Wholesale Shared Services
Area of Expertise:
Technology
Reference Code:
JR-0000100321
Contract:
Permanent
Take a look at the map to see what’s nearby. Train stations & bus stops, gyms, restaurants and more.
Explore locationJoin us as a Delivery Lead/Senior Data Engineer 3. At Barclays, we don’t just adapt to the future, we create it. As a Delivery Lead/Senior Data Engineer 3 you will 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.
To be a successful Engineering Manager, you should have experience with:
Proven leadership experience delivering enterprise‑scale data platforms and architectures in complex, regulated environments. Deep expertise in cloud data architecture and distributed computing paradigms, with strong hands‑on background in AWS data platforms, including Glue, Lambda, S3, Redshift, Athena, and Databricks.
Strong experience with modern analytical data platforms such as Snowflake, including architecture design, data modelling, workload optimization, and cost governance. Advanced knowledge of data modelling techniques, including dimensional modelling, schema evolution, and design patterns for analytics, reporting, and downstream consumption.
Demonstrated ability to define and govern data architecture standards, reference architectures, and engineering frameworks across multiple teams. Strong understanding of cloud security, IAM, data access controls, and platform governance, with experience implementing fine‑grained data security using tools such as Immuta.
Advanced proficiency in Python, PySpark, and SQL, with the ability to guide teams on performance optimization and scalable design rather than individual contribution alone. Experience leading DevOps and CI/CD strategies for data platforms using tools such as Jenkins and GitLab, embedding quality, automation, and reliability into delivery pipelines.
Strong knowledge of data governance, metadata management, data quality, and data mesh concepts, with the ability to influence enterprise‑wide adoption. Ability to communicate complex technical concepts clearly to senior leadership, influencing architectural and investment decisions.
Additional relevant skills given below are highly valued:
Leadership exposure to real‑time and event‑driven architectures, including Apache Kafka, Spark Streaming, or similar technologies. Strategic understanding of DBT (Data Build Tool) and analytics engineering practices for scalable transformation and modelling.
Experience operating data platforms within regulatory, risk‑controlled, or large financial services environments. Experience supporting or enabling machine learning and AI workloads (including model training, inference, or feature pipelines) in partnership with Data Science or AI teams.
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 in Pune.
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
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.