Barclays Data & Analytics Job Alerts 2025 – Apply Soon!

Qualifications

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.

To be successful as Data Governance Analyst, you should have experience with:

• Data and Record governance, data controls, data lineage and associated methodologies.
• Experience in data products, cloud and data warehouses
• Business Domain (Retail or Banking) and Regulatory reporting experience.
• Working in a regulated environment and solid understanding of data and control risk management.
• SQL and related skill set Knowledge is required

Additional relevant skills include:

• Understanding of different technologies around the execution of data control.
• Ability to proactively drive change.
• Exceptional stakeholder management skills to be able to maintain collaborative working relationships with key senior stakeholders.
• Experience of working in multiple large teams delivering complex services involving the highest standards of resilience, risk and governance controls.
• Proficiency in data analytics and insight generation to derive actionable insights from data.
• AWS (Any Cloud) and related components and Python Skill set will have added advantage.

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.