Data Engineer/Analyst-Location Flexible

This role is responsible for supporting and leading data manipulation and reporting, quality assurance, documentation and internal/client communication projects.

Position will require development/programming skills in one of the following. Python, C, Java, Sas

Key Responsibilities/Activities

1. DATA ANALYSIS

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• Carry out and when required, supervise others carrying out, the extraction, formulation and manipulation of data to create the structured samples necessary to address business requirement.
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• Interpret and, where appropriate, supervise others in the interpretation of data specifications.
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• Apply the most relevant method to solve client’s problem while balancing data quality and project timeline
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• Experiments with alternative solutions to discover improvement opportunities
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• Develops creative solutions that better utilize Experian and client data and produce new insights
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• Ensure quality and accuracy of own work and the work of any junior data engineer on the project.
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• Produced analysis is accurate and completed to agreed timescales, resulting in positive feedback from client/customer.
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• Follow Business Line procedures and processes throughout the data extraction, formulation and manipulation process, ensuring all work is produced to the agreed specification, and meets all requirements.
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• Take responsibility for the production of high quality results documentation.
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• Identify and resolve data problems, producing appropriate analysis to verify results.
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• Identify potential gaps in own technical/business knowledge that might compromise the deadlines. Work with Project Managers or Consultant to plan timely steps to fill gaps.
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• Challenge existing processes and recommend improvements.
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• Share findings with peers from other VM Teams and management where required.
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• Prepared to communicate ideas in knowledge sharing forums.
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• Ensure the quality of all data sent to clients/customers (e.g. project development samples; retrospective bureau data and Bureau Score data (if applicable))
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• Analyse and confirm the integrity of source data to be evaluated.

2. PROJECT AND TIME MANAGEMENT (30%) - Plan, organise and complete own workload to meet project commitments within agreed schedules

• Input into the review and assessment of client/customer requirements to produce a data project specification.
• Produces data specifications.
• Anticpates project needs and actively collects information and resources with assistance
• Liaise with other internal and external project management groups to ensure project is delivered as part of complete solution.
• Input into the accurate assessment of the work that needs to be undertaken to define and maintain a project plan.
• Plan, organize and complete own workload and supervise, where appropriate, the workload of any junior data engineer on the project, to meet project commitments within agreed schedules.
• Is able to manage multiple tasks simultaneously without compromising the quality of the final deliverables.
• Provide pro-actively status reports and progress updates to Project Manager or Consultant as required, for all projects/tasks.
• Contribute to the preparation of regular project status reports to both internal and external parties.
• Proactively identify potential risks in achieving project timescales, taking pro-active action to minimize risk.
• Recognize when issues or problems need to be escalated.
• Maintain accurate time recording to projects in the appropriate internal time tracker software
• Effectively uses project management / planning tools
• Proactively use time recording data to identify inefficiencies in project work and recommend improvements
• Implement appropriate quality control procedures for all analysis reporting
• Reduce error rate & re-run frequency. Meet both the analytical & business objective
• Reconcile analytical projects with Business Unit objectives and proactively propose solutions to meet clients needs.
• Collaborate with internal and external clients to determine the appropriate performance measures and statistical metrics to be applied during the analysis project.
• Produce and implement project plans for analytical processes.
• Generate reports following quality control procedures to document analysis findings

3. MANAGING CLIENT AND INTERNAL RELATIONSHIPS (30%) - Support the project team by understanding the client’s requirements

• Communicate with client and/or other departments/divisions within Experian to help ensure accurate and timely implementation of project work, and to enable them to manage client expectations.
• Ensure full understanding of the client’s/customer’s requirements.
• Ensure that all written and verbal communication is clear and professional.
• Build and maintain positive day to day client/customer relationships at peer level.
• Together with the Project Manager or Consultant take part in client reviews and delivery meetings. Meet with clients/customers to present results and conclusions in both written and verbal form.
• Take responsibility for the resolution of client/customer problems or issues.
• Identify and feedback opportunities outside of the initial scope of the project to the Project Manager or Consultant.
• Be aware of and provide insight for all projects including those designed and executed by other Analytics team members for these assigned accounts.
• Coordinate data receipt and delivery with internal and external clients.

4. TEAMWORK & KNOWLEDGE SHARING (5%) -

• Demonstrate ability to lead assigned departmental strategic initiatives
• Priorities own, and where appropriate others workload and communicate this effectively to the Supervisor or Resources Manager to provide input into resource plans.
• Mentor junior Data Engineers in the use of software and data coding and analysis methodologies, providing explanations of business requirement specifications to facilitate understanding of the clients/customers’ objectives.
• Work on background internal projects to review and optimize all internal technical processes during analytical project development and delivery.
• Contribute to and/or produce technical tools and respective user manuals to improve all technical aspects of the project work.
• Share expertise with others and continually strive to improve overall contributions to the department.
• Educate the team as well as sales on the different elements involved in building successful analytical solutions.
• Work with consultant and expert level statisticians to initiate “think tank” sessions.
• Participate in training activities to assist and develop lesser-experienced staff, provide guidance in application of statistical methods.
• Actively engage both as a presenter and an audience member in Knowledge Sharing meetings.
• Actively develop materials for participation in Knowledge Share and relevant roundtable discussions
• Attend and be an active contributor in Department meetings that discuss results, issues encountered with various projects, and ideation.

5. PERSONAL DEVELOPMENT (5%) - Improve personal and professional competencies and technical/analytical skills through continual learning.

• Maintain and action agreed personal development plan.
• Seek extensive feedback to improve skills, knowledge and competencies as part of the feedback process.
• Maintain awareness of latest technical and market developments in the area of data manipulation.
• Actively seek to further improve coding skills.
• Actively seek to develop competency/knowledge of both software and analytics (moderate understanding)
• Keep abreast with recent developments in analytical methods and software tools through internal and external training and expand technical expertise