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ROLE PROFILE Role Title: Data Quality Analyst Grade: P3 Reports to: Data Quality Manager Direct Reports: N/A Directorate: Fundraising and Marketing Location: Angel- Head Office, Islington London Date: February 2016 Summary of the Role’s Main Purpose: This position will measure and analyse a variety of data held for Fundraising and Marketing, ensuring that supporter details are accurate and meet CRUKs quality standards. In addition this role will represent Data Services on data quality issues arising from incidents and change, investigating the root cause of problems to address anomalies. On behalf of Data Services and the Fundraising & Marketing (F&M) teams, the Data Quality Analyst will support the Data Quality identification and improvement work-stream. Balancing pro-active data quality management with reacting to incidents and stakeholder requirements, the role will have a particular focus on data quality, both scenario based and data quality improvement initiatives to drive forward the quality of our data. Key Responsibilities: Lead on the investigation of data quality and other data incidents, documenting them according to the required standards utilising the prescribed methods and tools Ensure data quality is maintained against Cancer Research UK’s supporter data quality standards through pro-active identification and correction Co-ordinate and apply data quality measurements, analysis and data modelling techniques, based upon a detailed understanding of our supporter requirements and business needs, in order to establish, modify or maintain data structures and their associated components Create, test and manage (scenario planning and impact assess) data quality rules to identify data quality issues using Informatica; whilst liaising with stakeholders from technical teams Run a programme of data cleansing and merging to retain the reliability and validity of our data supporter asset Carry out root cause analysis on data issues or problems as they arise Analyse automatically generated reports to determine the extent and nature of data quality issues Ensure that all Data Quality requirements are satisfied and reported on and all standards are completed against the agreed scope, on time and on budget Effectively measure the cost and benefits of data quality, make recommendations for data quality improvements and manage the change process Pro-actively design, create, implement and administer data quality monitoring jobs Manage and deliver data quality reports based on searches and data extracted Document to Cancer Research UK standards the data quality baseline expectations Apply your data experience of handling large complex data sets to identify inaccuracies & define remediation plans Date: 28th January 2016 Document1 Page: 1/2 Apply principles of data profiling, data quality, using applications and sources such as Informatica, SAS, Talend, Cygnus, Read Group, Experian Key Technical Skills, Knowledge and Experience: Expert knowledge of data manipulation and query tools for example Microsoft and Oracle through TSQL/PL-SQL Experience of modelling and understanding data and its use and application for example: ERD, Logical and Physical data models, statistical process control, relational data modelling, use cases Experience of measuring data quality, setting up data quality scorecards and using statistical methods to identify poor quality data in large data sets Experience of identifying, assessing, correcting and managing data quality issues, which could result in; bad data quality, time or cost over-runs, failure to deliver products which are fit for purpose, missing compliance targets Experience of identifying duplicate records, ideally using Informatica Proficient in the selection and application of data and information gathering methods, tools and techniques which are appropriate to the information required and the sources available Proven Data Analysis/Mining/profiling skills and expertise in a CRM environment Expert knowledge in MS Excel and MS Access with Visual basic Working knowledge of descriptive statistics Good knowledge and understanding of the Data Management lifecycle Proven and applied understanding of Data Quality principles and practices Organised, disciplined and analytical problem solver, able to support and drive Data Quality goals Demonstrable experience of stakeholder management, through effective verbal and written communication skills Proven ability of making pragmatic decisions whilst still adhering to Data Quality principles and standards Experience of carrying out data quality tests Ability to work to tight deadlines and cope with pressure Excellent attention to detail and accuracy Methodical and structured approach to work Knowledge of different types of database architecture and the products which use each typ. Examples: relational, hierarchical, matrix, object-oriented Knowledge of data warehouse concepts Working experience of Informatica Analyst and Developer desired Date: 28th January 2016 Document1 Page: 2/2