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Join Barclays as a Chief Data Office Data Analyst, where you will play a pivotal role in turning complex, high-volume datasets into clear, actionable insight that drives both strategic direction and day-to-day operational decisions across the organisation. You will work across analytics, governance, and business change—helping ensure that data used across risk, finance, and regulatory reporting is accurate, trusted, and well-controlled. In this role, you will translate your findings into compelling visualisations, reports, and narratives that enable stakeholders to act with confidence. Beyond analysis, you will play a key role in embedding data standards into change programmes, supporting regulatory reviews and internal audit engagements, and partnering with Chief Data & Analytics Office (CDAO) teams to deliver trusted data products at scale.
Job Responsibility
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
Requirements
Analytical and problem-solving skills with the ability to interpret, cleanse, and synthesise complex datasets
Proven experience in data profiling, issue resolution, and delivering actionable insights from large datasets
Ability to lead or support stakeholder meetings and translate business needs into clear analytical requirements
Advanced proficiency in data analysis and visualisation tools, including SQL, Python, Tableau, and Excel
Ability to influence decision-making through data storytelling and clear visual communication
Understanding of statistical and analytical techniques to identify trends, patterns, and anomalies
Experience conducting root cause analysis to identify and resolve data quality issues effectively
Experience engaging with stakeholders across technical and business teams to align priorities and drive outcomes
Practical understanding of data governance, data lifecycles, and data quality management within a financial services environment
Experience working in Agile environments, with familiarity in tools such as Jira
Nice to have
Experience supporting regulatory reporting, audit reviews, or risk data governance within a financial institution
Understanding of data and records management principles and their importance in regulated environments
Experience working with scaled Agile frameworks and cross-functional delivery teams
Familiarity with data pipeline design and data preparation techniques
Experience partnering with data governance or data architecture teams to improve data quality and accessibility
Awareness of risk management principles related to data handling, controls, and compliance