VP - Data Engineer

Purpose of the role

To enable data-driven strategic and operational decision making through extracting actionable insights from large datasets, performing statistical and advanced analytics to uncover trends and patterns, and presenting findings through clear visualisations and reports.

Accountabilities

• Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification, documenting data sources, methodologies, and quality findings with recommendations for improvement
• Designing and building data pipelines to automate data movement and processing.
• Apply advanced analytical techniques to large datasets to uncover trends and correlations, develop validated logical data models, and translate insights into actionable business recommendations that drive operational and process improvements, leveraging machine learning/AI.
• Through data-driven analysis, translate analytical findings into actionable business recommendations, identifying opportunities for operational and process improvements.
• Design and create interactive dashboards and visual reports using applicable tools and automate reporting processes for regular and ad-hoc stakeholder needs.

Vice President Expectations

• To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
• If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others..
• OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
• Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
• Manage and mitigate risks through assessment, in support of the control and governance agenda.
• Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
• Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
• Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
• Adopt and include the outcomes of extensive research in problem solving processes.
• Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

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 “VP- Data Engineer" at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.
You may be assessed on the key critical skills relevant for success in role, such as experience with, skills to meet business requirement as well as job-specific skillsets.

To be successful as a “VP- Data Engineer", you should have experience with:

Basic/ Essential Qualifications:

• Technologies: Application development using Python, C/C++. Knowledge of Data analysis, Data Engineering. Experience in Messaging technologies (KAFKA), Solace, microservices based architecture, API development, SQL Database, DevOps technologies.
• Infrastructure & Cloud Architecture: Design, provision, and manage scalable AWS infrastructure using Infrastructure as Code (CloudFormation, Terraform). Experience with multi-account strategies, VPC design, transit gateways, and hybrid cloud architectures. Implement API Gateway patterns including REST/WebSocket APIs, custom authorizers, and integration with Lambda/backend services.
• Container Orchestration: Build production-grade containerized applications with Docker (multi-stage builds, image optimization, security scanning). Deploy and manage Kubernetes clusters including pod scheduling, resource management, service mesh integration, ingress controllers, persistent storage, and cluster autoscaling.
• CI/CD Pipeline Engineering: Architect end-to-end GitLab CI/CD pipelines with multi-stage deployments, artifact management, and environment promotion strategies. Implement automated quality gates integrating SonarQube (code coverage, technical debt analysis) and Veracode (SAST/DAST scanning). Configure pipeline-as-code, shared libraries, and deployment strategies (blue-green, canary, rolling updates).

Desirable skillsets/ good to have:

• AI/ML: Good to have knowledge about AI/ML technology.
• NoSQL Database: MongoDB.
• Risk Management: Knowledge about Investment banking, risk management, securitized products.
• Drive platform initiatives.
• Work with senior stakeholders (VP/Director level).
• Mentor engineering teams. 
• AWS Certified Solutions Architect.
   

This role is based out of Pune.