Excellent contract role opens with major bank for experienced Data Analyst to act as a data champion for data governance and quality, by raising awareness of data management best practices and the application of data controls, to help the business embed frameworks, reduce data risks, and unlock the value of data.

This includes contributing to data and business analysis and documenting data requirements related to data management, EUDA management and Master Data management, supporting the establishment of the Bank's operating model for data ownership and the Bank's data governance committee structures.

The role reports directly to the Data Technical Lead and is part of a small team of Data Analysts responsible for embedding best practice data governance and quality practices across the Bank whilst also helping support the wider change initiatives across the organisation.

Main Responsibilities

• Undertake activities to support the enterprise-wide data catalogue, to document business glossary definitions, taxonomies, ontologies and alignment to conceptual data models and standards.
• Contribute to the development and maintenance of the metadata management system and data dictionaries, working collaboratively with data owners and their teams.
• Document source to target technical data lineage and data quality controls along the data flow for reports and business outputs.
• Analyse data quality root causes and understand business problems, partnering with business and technology teams to remediate data quality issues.
• Build data outcomes using technical data profiling, mining, score carding utilising data analysis skills.
• Undertake quantitative analysis using SQL, Excel, SAS, Python experience to source, analyse, normalise and process data across multiple data sets.
• Conduct data analysis to study, analyse and interpret large volumes of transactional data, question authenticity as well as construct solutions.
• Interpret data flows and models to understand lineage gaps and resolve missing data quality controls.
• Apply best practice data quality and metadata management principles to resolve data quality issues and address underlying causes.
• Support the development of trusted sources for critical data, collaborating with other stakeholders including data consumers, data producers, data owners and stewards to define requirements.
• Be enthusiastic about data quality and continuously strive to promote data quality through the development of system and process controls.
• Apply technical thinking with regards to analysing complex data sets and extracting meaningful insights for data quality management
• Demonstrate detailed scrutiny of technical and business data flows and transformations to operationalise data lineage management.
• Demonstrate experience leading data management activities to implement data frameworks and establish data controls and monitor their effectiveness.
• Experience of leading data quality initiatives that have provided tangible efficiencies and/or business value.
• Experience of data quality management, master data management and reference data management
• Working knowledge of statutory frameworks such as CCPA, GDPR, BCBS and Data Protection Act
• Ability to create positive relationships and communicate with a range of stakeholders.
• Demonstrate experience of problem-solving skills related to data profiling analysis, score carding and error detection.
• Experience using data visualisation tools to present complex analysis is essential eg Power BI, Tableau, Qlikview.
• Strong presentation skills both written and oral, experienced in presenting complex data concepts to a business audience ie running workshops and formal data governance meetings.
• Knowledge and understanding of master data elements and processes, understanding of static versus transactional data challenges.
• Experience and/or knowledge of data quality and lineage tools: Ab Initio, Collibra, Informatica, IBM MDM etc.
• Experience of data modelling is ideal but not essential.
• (Optional) Practical experience and an understanding of both Agile and Waterfall ways of working
• (Optional) Experience in modelling business processes, preferably BPMN or other industry modelling standards
• (Optional) Experience using a variety of software tools such as JIRA, Confluence, MS Visio etc.

Bank Banking Business Data Analyst