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Join us as an AVP – Fraud Data Strategy at Barclays, where you will play a critical role in enabling large‑scale data modernization and cloud migration initiatives. You will support businesses on their data transformation journey by designing and delivering robust data migration and data quality solutions, while ensuring strong governance, risk management, and measurable business outcomes. You will also act as a trusted advisor, translating complex data and AI capabilities into tangible value across the organization.
Job Responsibility:
Investigation and analysis of data issues related to quality, lineage, controls, and authoritative source identification
Execution of data cleansing and transformation tasks to prepare data for analysis
Designing and building data pipelines to automate data movement and processing
Development and application of advanced analytical techniques, including machine learning and AI, to solve complex business problems
Documentation of data quality findings and recommendations for improvement
To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function
Consult on complex issues
providing advice to People Leaders to support the resolution of escalated issues
Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda
Take ownership for managing risk and strengthening controls in relation to the work done
Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function
Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy
Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively
Communicate complex information
Influence or convince stakeholders to achieve outcomes
Requirements:
Expertise in enterprise data strategy, data engineering, cloud migration, or related roles
Strong understanding of modern data architectures, including data lakes, data warehousing, metadata management, and data pipelines
Experience with cloud platforms such as AWS, Azure, or Google Cloud, and data warehousing concepts
Hand on experience with programming language – Python/SAS/SQL
Expertise in databricks, including notebooks, Delta Lake, Spark, and orchestration
Hands‑on experience with GitLab for code management, governance controls, and change management activities
Familiarity with Agile delivery methodologies and tools such as Jira and Confluence
Experience working with data governance, master data management (MDM), and data quality frameworks
Proven background as a management consultant with strong exposure to data transformation and data migration engagements
Ability to act as a strategic advisor, supporting business teams through their data transformation journey by implementing enterprise‑scale data management and migration solutions