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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
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 Full Stack Data Engineer at Barclays, where you will design and build innovative applications and data solutions that enable secure data provisioning, masking, synthetic data generation, and test data management across the organization. You will work across the full technology stack, from backend services and APIs to frontend applications, while supporting DevOps practices and ensuring high standards of security, scalability, and reliability.
To be successful as a Full Stack Data Engineer, you should have experience with
Programming & Development
Hands-on software development experience with strong analytical and problem-solving skills.
Python (backend development using frameworks such as Django, Flask, or FastAPI).
Advanced Oracle/SQL skills, including database design, query optimisation, and stored procedures.
Frontend technologies such as React/Angular and JavaScript.
RESTful API design and development.
Shell scripting.
Ability to write clean, maintainable, reusable, and well-documented code.
DevOps & Infrastructure
CI/CD pipeline implementation and management.
GitLab (version control, merge requests, and pipeline management).
Unix/Linux environments and command-line operations.
Chef (Cookbooks, Recipes, etc.).
Experience in deployment automation, release support, and environment troubleshooting.
Understanding of application monitoring, logging, and basic infrastructure support practices.
Data Skills
Understanding of Data Masking and Data Anonymisation techniques.
Experience with Synthetic Data Generation algorithms and methodologies.
Experience working with structured data, relational databases, and large datasets.
Competence in data modelling, schema design, data validation, and data quality controls.
Ability to support secure data provisioning, transformation, and controlled data movement across environments.
Awareness of data privacy and regulatory requirements, including GDPR and CCPA.
Some other highly valued skills may include:
SonarQube, Wiz for code quality
Understanding of Cloud platforms.
Ability to work in Agile environments
Knowledge of Unit and Integration testing
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.
The role is based out Pune.
You'll no longer be considered for this role and your application will be removed from the employer's inbox.