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
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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 solid 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‑nativ

📌 Data Engineering Lead (Pune Division)
🏢 Barclays
📍 Pune Division