Head of Banking Data, AI and Analytics Platform

Barclays•Jefferson, CO

About The Position

The purpose of this role is to lead and manage engineering teams, providing technical guidance, mentorship, and support to ensure the delivery of high-quality software solutions. This includes driving technical excellence, fostering a culture of innovation, and collaborating with cross-functional teams to align technical decisions with business objectives. The role involves managing a business function, contributing to strategic initiatives, and influencing policy and procedures. The Head of Banking Data, AI and Analytics Platform will manage the direction of a large team or sub-function, leading other people managers and embedding a performance culture. They will also lead organization-wide projects, act as a deep technical expert, and thought leader, identifying new ways of working and collaborating cross-functionally. This role requires training, guiding, and coaching less experienced specialists, and providing information affecting long-term profits, organizational risks, and strategic decisions. The position demands providing expert advice to senior functional management and committees to influence decisions made outside of their own function, managing resourcing, budgeting, and policy creation for a significant sub-function. Fostering and guiding compliance, ensuring regulations are observed, and maintaining adherence to relevant processes are critical. The role requires a focus on the external environment, regulators, or advocacy groups to monitor and influence on behalf of Barclays. Extensive knowledge of how the function integrates with the business division/Group to achieve overall business objectives is necessary, along with a comprehensive knowledge of industry theories and practices within their discipline, up-to-date sector/functional knowledge, and insight into external market developments/initiatives. Interpretative thinking and advanced analytical skills are needed to solve problems and design solutions in complex/sensitive situations. Management authority will be exercised to make significant decisions and certain strategic decisions or recommendations within their area. Negotiation and influence with senior stakeholders, both internally and externally, are key. The role serves as the principal contact point for key clients and counterparts in other functions/business divisions and as a spokesperson for the function and business division. Senior leaders are expected to demonstrate specific leadership behaviors (Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others) and Barclays Values (Respect, Integrity, Service, Excellence and Stewardship) and the Barclays Mindset (Empower, Challenge and Drive). This is a senior data leader role with experience building and scaling enterprise data functions, proven track record in building and implementing scalable model infrastructure, and platform ownership for the Investment Banking and Wholesale Lending Data lake on Barclays Enterprise Data Platform (EDP). Accountability includes delivering accurate, reliable, high-quality data within SLA/OLA for various model/non-model use cases, designing and building strategic Banking and Wholesale Lending Data Products, meeting various CEO/CFO/CRO MI/reports/metrics, ensuring a highly resilient Data Platform, and managing financial budgets, resource and cost planning, forecasting, tracking business benefits, and ensuring return on investment. The role requires simplifying and paraphrasing complex technical concepts for C-suite leaders, demonstrating business value, and possessing strong stakeholder management skills. The ability to lead large teams (50+ to 150+ colleagues) and accountability for establishing Data Governance, Data Entitlements, and Data Policies for the platforms are essential.

Requirements

Senior data leader with experience building and scaling enterprise data functions.
Proven track record in building and implementing scalable model infrastructure.
Platform owner accountable for building and evolving the Investment Banking and Wholesale Lending Data lake on Barclays Enterprise Data Platform (EDP).
Accountability to deliver Accurate, Reliable, High Quality data from the Data Lake within SLA/OLA for various Model/ Non Models (MI, Reports, Dashboards) use cases for business stakeholder areas.
Designing and building the strategic Banking and Wholesale Lending Data Products on Barclays EDP.
Data Platform Owner accountable for various SLAs/OLAs for delivering and receiving data from various stakeholder areas within the Barclays ecosystem; accountable to meet various CEO/CFO/CRO MI/reports/metrics in a timely manner.
Accountable to ensure and maintain a highly resilient Data Platform for Investment Banking and Lending.
Accountable for managing and tracking financial budgets for the area, bottom up resource and cost planning, forecasting costs accurately, tracking business benefits and ensuring return on investment.
Simplify, paraphrase, translate complex technical concepts for C-suite leaders with clear examples to articulate the business value delivered.
Senior stakeholder management skills.
Ability to lead large teams – 50+ to 150+ colleagues.
Accountability for establishing Data Governance, Data Entitlements and Data Policies for the platforms.
AWS Certified Solution Architect and/or Data Engineer.
Adopts AI development tools such as Claude Code, Cursor, Git Lab Duo.
Proven track record of delivering Data Products on Enterprise Data Platforms on Public and Private Cloud infrastructure.
Ability to both, directly build and technically direct the development of E2E Data, Analytics and AI products.
The ability to code production quality solutions using both, Java and Python.
Ability to build complex models using Porch or TensorFlow.
Ability to manage performant SQL databases and ability to finetune databases.
Mastery of ML/Data Science skills – proven track record in Data Science/ML with expertise in Python, SQL and Deep Learning libraries (TensorFlow, Keras, PyTorch).
Ability to build and deploy LLM and SLM driven workflows and NLP solutions that are scalable, compliant and production ready.
Deep familiarity with information security solutions in the context of Enterprise AI.
Expertise in DataBricks, SnowFlake, Airflow, DBT will be preferred.
Deep expertise in data privacy, access management and policy governance.
Hands on skills in data catalog tools with exposure to continuously maintaining the health of data quality (accuracy/ completeness) controls and lineage.

Nice To Haves

Expertise in DataBricks, SnowFlake, Airflow, DBT will be preferred.

Responsibilities

Lead and manage engineering teams, providing technical guidance, mentorship, and support.
Ensure the delivery of high-quality software solutions.
Drive technical excellence and foster a culture of innovation.
Collaborate with cross-functional teams to align technical decisions with business objectives.
Oversee timelines, team allocation, risk management, and task prioritization.
Ensure the successful delivery of solutions within scope, time, and budget.
Mentor and support team members' professional growth, conduct performance reviews, and provide feedback.
Evaluate and enhance engineering processes, tools, and methodologies.
Translate business requirements into technical solutions.
Enforce technology standards, facilitate peer reviews, and implement robust testing practices.
Manage a business function and contribute to function-wide strategic initiatives.
Manage the direction of a large team or sub-function, leading other people managers.
Lead organization-wide projects and act as a deep technical expert and thought leader.
Train, guide, and coach less experienced specialists.
Provide expert advice to senior functional management and committees.
Manage, coordinate, and enable resourcing, budgeting, and policy creation for a significant sub-function.
Foster and guide compliance and ensure regulations are observed.
Focus on the external environment, regulators, or advocacy groups to monitor and influence on behalf of Barclays.
Demonstrate extensive knowledge of how the function integrates with the business division/Group.
Maintain broad and comprehensive knowledge of industry theories and practices.
Use interpretative thinking and advanced analytical skills to solve problems and design solutions.
Exercise management authority to make significant decisions and strategic recommendations.
Negotiate with and influence stakeholders at a senior level.
Act as principal contact point for key clients and counterparts.
Act as a spokesperson for the function and business division.
Demonstrate leadership behaviors to create an environment for colleagues to thrive.
Build and scale enterprise data functions.
Build and implement scalable model infrastructure.
Own and evolve the Investment Banking and Wholesale Lending Data lake on Barclays Enterprise Data Platform (EDP).
Deliver accurate, reliable, high-quality data from the Data Lake within SLA/OLA for various Model/Non-Model use cases.
Design and build strategic Banking and Wholesale Lending Data Products on Barclays EDP.
Meet various CEO/CFO/CRO MI/reports/metrics in a timely manner.
Ensure and maintain a highly resilient Data Platform for Investment Banking and Lending.
Manage and track financial budgets for the area, bottom-up resource and cost planning, forecasting costs accurately, tracking business benefits, and ensuring return on investment.
Simplify, paraphrase, and translate complex technical concepts for C-suite leaders with clear examples to articulate business value.
Manage performant SQL databases and finetune databases.
Build and deploy LLM and SLM driven workflows and NLP solutions that are scalable, compliant, and production ready.
Manage data privacy, access management, and policy governance.
Maintain the health of data quality (accuracy/completeness) controls and lineage.
Establish Data Governance, Data Entitlements, and Data Policies for the platforms.