Pune · Staff/Principal
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Purpose of the role
To design, develop, and implement solutions to complex business problems, collaborating with stakeholders to understand their needs and requirements, and design and implement solutions that meet those needs and create solutions that balance technology risks against business delivery, driving consistency.
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 Architect Barclays, responsible for supporting the successful delivery of Location Strategy projects to plan, budget, agreed quality and governance standards. You'll spearhead the evolution of our digital landscape, driving innovation and excellence. You will harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences.
To be successful as a Data Architect you should have experience with: -
Design and govern end‑to‑end data architectures, covering ingestion, processing, storage, and analytics.
Define lakehouse and distributed data processing architectures leveraging Apache Spark/Airflow on AWS (e.g. EMR / Glue).
Establish logical and physical data models optimised for analytics and large‑scale data processing.
Ensure architectural alignment with enterprise data standards and cloud best practices.
Partner with data engineering teams to define Spark‑based data processing patterns for batch and large‑scale transformations.
Guide development of Python‑based data pipelines for ingestion, transformation, and orchestration.
Support optimisation of SQL‑based analytics, including complex queries, performance tuning, and consumption‑layer design.
Bachelor’s degree in computer science, Engineering, or related discipline.
AWS certifications preferred.
Strong experience designing Cloud‑based data platforms in enterprise environments.
Hands‑on experience with Apache Spark, Airflow for large‑scale data processing and transformation.
Strong programming experience in Python for data engineering and pipeline development.
Advanced SQL skills, including:
Analytical queries.
Performance optimization.
Data validation and reconciliation.
Solid understanding of data modelling, distributed data processing, and analytics workloads.
Some other highly valued skills may include: -
Deep knowledge of AWS data services.
S3, Glue, Athena, Redshift, EMR, Lake Formation.
Experience designing batch and analytical processing architectures using Spark and SQL.
Good to have Astronomer and Databricks knowledge.
Understanding of data ingestion, hydration, curation, and consumption patterns.
Proven experience in enterprise data architecture and governance.
Strong understanding of data quality, lineage, metadata, and security controls.
Experience working in regulated environments (banking / financial services preferred).
Ability to translate business requirements into scalable Spark / SQL‑based data solutions.
Strong stakeholder communication and architecture documentation skills.
Comfortable operating across architecture, engineering, and delivery teams.
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 Pune.
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