VP – Data Product, Governance & AI/ML Enablement Lead

Posted 18 Days Ago
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Pune, Maharashtra, IND
In-Office
Expert/Leader
Fintech • Financial Services
The Role
Lead design, build and maintenance of data architectures, pipelines, warehouses and lakes; enable ML lifecycle by preparing governed datasets, collaborating with data scientists, and driving data governance, lineage, access controls and analytics-ready schema design.
Summary Generated by Built In
Job Description

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

  • Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
  • Design and implementation of data warehoused and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
  • Development of processing and analysis algorithms fit for the intended data complexity and volumes.
  • Collaboration with data scientist to build and deploy machine learning models.

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 Product, Governance & AI/ML Enablement Lead at Barclays where you will spearhead the evolution of our infrastructure and deployment pipelines, driving innovation and operational excellence. You will harness cutting-edge technology to build and manage robust, scalable and secure infrastructure, ensuring seamless delivery of our digital solutions. 

To be successful as a  VP – Data Product, Governance & AI/ML Enablement Lead, you should have experience with:

  • Data Engineering (Primary Capability)

  • Distributed data processing (Spark / Databricks / similar)

  • Data pipeline design (batch + streaming)

  • Data API / consumption layer experience

  • Cloud data platforms (AWS preferred: S3, Athena, Glue, etc.)

  • Data Modelling & Data Architecture

  • Strong SQL proficiency

  • Logical & physical data modelling

  • Domain-driven data design (aligned to business entities)

  • Schema design for analytics & consumption

  • AI/ML Enablement & Data for Intelligence

  • Strong understanding of ML data lifecycle:

  • Feature engineering datasets

  • Training vs inference data needs

  • Ability to collaborate with Data Scientists / AI teams

  • Experience preparing high-quality, governed datasets for ML use cases

  • Data Governance & Data Product Thinking

  • Ownership, lineage, metadata management

  • Data quality controls and DQ framework

  • Entitlements / access control patterns

  • Auditability & regulatory awareness

  • Data catalogue / discovery concept

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 of Pune.

Skills Required

  • Data Engineering (primary capability)
  • Distributed data processing (Spark / Databricks / similar)
  • Data pipeline design (batch and streaming)
  • Data API / consumption layer experience
  • Cloud data platforms (AWS preferred: S3, Athena, Glue, etc.)
  • Data modelling and data architecture (logical & physical)
  • Strong SQL proficiency
  • Domain-driven data design aligned to business entities
  • Schema design for analytics and consumption
  • AI/ML enablement and understanding of ML data lifecycle
  • Feature engineering dataset design and training vs inference data needs
  • Experience preparing high-quality, governed datasets for ML use cases
  • Data governance and data product thinking (ownership, lineage, metadata)
  • Data quality controls and DQ framework
  • Entitlements and access control patterns
  • Auditability and regulatory awareness
  • Data catalogue / discovery concepts
  • Ability to collaborate with Data Scientists / AI teams
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The Company
HQ: London
83,500 Employees

What We Do

Barclays is a British universal bank. We are diversified by business, by different types of customers and clients, and by geography. Our businesses include consumer banking and payments operations around the world, as well as a top-tier, full service, global corporate and investment bank, all of which are supported by our service company which provides technology, operations and functional services across the Group. With over 325 years of history and expertise in banking, Barclays operates in over 40 countries and employs approximately 83,500 people. Barclays moves, lends, invests and protects money for customers and clients worldwide.

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