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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.
Join us as a Data Engineering Lead. At Barclays, innovation isn’t just encouraged; it’s expected. You will be required to have an experience in SOLD Simplification. It is a multiyear initiative to make the platform compliant to most valuable environment, hardware refresh and removing redundant functionalities. You will be required to lead the overall engineering & development of this initiative. You will be an Engineering Lead and required to coordinate & support requirement Discovery, initiative & delivery planning, roadmap and stakeholder management.
To be successful as a Data Engineering Lead, you should have experience with:
Leading large‑scale data engineering initiatives on modern cloud data platforms, delivering resilient, governed, and audit‑ready data products in regulated banking environments.
Owning end‑to‑end data delivery across ingestion, transformation, quality, lineage, and consumption, with strong accountability for reliability, SLAs, and production stability.
Driving adoption of standardized engineering practices (SDLC, CI/CD, controls, documentation) across multiple teams and portfolios within an enterprise data platform.
Partnering with Product, Risk, Technology Control, and Business stakeholders to shape data strategy and translate regulatory and business outcomes into scalable architectures.
Exposure in Abinitio, Oracle AWS technologies.
Understanding of the Cards ecosystem.
Working knowledge of DBT, Databricks and Airflow.
Deep expertise in Python, SQL, and modern data engineering frameworks, with a track record of building and governing complex transformation pipelines at scale.
Some other highly valued skills may include:
Strong understanding of data quality, metadata, lineage, and observability, and the ability to institutionalize these as platform capabilities rather than team‑specific solutions.
Experience defining and enforcing engineering standards and architectural guardrails across lake house‑style or cloud‑native data platforms.
Proven leadership in coaching senior engineers, influencing across tribes, and driving engineering excellence in a federated enterprise model.
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 our Pune office.
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