At a Glance
- Tasks: Analyse data and support a major transformation programme at a leading university.
- Company: The University of Sheffield, a world-class institution with a diverse community.
- Benefits: Competitive salary, generous leave, flexible working, and extensive discounts.
- Other info: Opportunities for personal development and a commitment to inclusivity.
- Why this job: Join a dynamic team and make a real impact on data-driven decisions.
- Qualifications: Experience in data analysis and strong problem-solving skills required.
The predicted salary is between 32080 - 36636 £ per year.
The University of Sheffield is a remarkable place to work. Our people are at the heart of everything we do. Their diverse backgrounds, abilities and beliefs make Sheffield a world-class university. We offer a fantastic range of benefits including a highly competitive annual leave entitlement, a generous pensions scheme, flexible working opportunities, a commitment to your development and wellbeing, a wide range of retail discounts, and much more.
Overview
The Data Analyst supports the delivery of data activities within a large-scale enterprise transformation programme, including the transition from SAP ECC to new platforms across HR, finance, procurement, and expenses. The role focuses on analysing data, identifying and structuring data issues, and supporting their resolution. Working with both business stakeholders and technical teams, the Data Analyst translates data findings into clear insights, helping the programme understand data challenges and make informed decisions. The role operates with a high degree of independence on defined tasks, while working alongside Senior Data Analysts on more complex issues.
Main duties and responsibilities
- Analyse legacy data (e.g. SAP ECC) across multiple functional domains to identify data quality issues such as completeness, accuracy, and consistency.
- Investigate data anomalies and support root cause analysis.
- Structure findings into clear problem statements, including issue, cause, and business impact.
- Manage and progress data quality issues through to resolution, maintaining clear documentation and tracking.
- Execute data cleansing activities in collaboration with business stakeholders, including resolving duplicate, obsolete, or inaccurate data.
- Support preparation of data for migration into target systems.
- Validate data extracts, transformations, and mappings.
- Participate in migration activities, including test cycles and mock migrations, and resolve data discrepancies.
- Work directly with business stakeholders to gather requirements, clarify issues, and support resolution of data challenges.
- Collaborate with IT teams and external delivery partners to investigate and resolve data issues.
- Act as a reliable point of contact for data-related queries within defined areas.
- Support definition and validation of data mapping for integrations and system transitions.
- Execute data testing, reconciliation, and validation activities pre- and post-migration.
- Understand how data supports reporting and analytics, identifying potential downstream impacts of data changes.
- Contributions to cleansed and migration-ready datasets.
- Data validation, testing, and reconciliation outputs.
- Accurate tracking and progression of data issues.
Person Specification
Our diverse community of staff and students recognises the unique abilities, backgrounds, and beliefs of all. We foster a culture where everyone feels they belong and is respected. Even if your past experience doesn't match perfectly with this role's criteria, your contribution is valuable, and we encourage you to apply.
Criteria
- Experience in data analysis within a business or technical environment.
- Strong analytical and problem-solving skills.
- Ability to investigate and interpret data issues.
- Experience working with data tools (e.g. SQL, Excel).
- Ability to communicate data findings clearly to both technical and non-technical stakeholders.
- Experience working with stakeholders across business and IT.
- Strong attention to detail.
- Comfortable working with ambiguity while progressing tasks independently.
- Practical and delivery focused, with an ability to balance analysis with delivery pace.
- Experience with ERP systems (e.g. SAP ECC).
- Exposure to data migration or transformation programmes.
- Experience with data mapping or integration activities.
- Familiarity with BI/reporting tools (e.g. Power BI, Tableau).
- Exposure to HR, finance, procurement, or expenses data domains.
Further Information
- Grade 6
- Work arrangement: Full-time
- Duration: Fixed-term until 31 July 2030
If you need any support, equipment or adjustments to enable you to participate in any element of the recruitment process, you can contact it-services-recruitment@sheffield.ac.uk.
Data Analyst in Sheffield employer: Dunhillmedical
The University of Sheffield is an exceptional employer, offering a vibrant academic environment where innovation in teaching and research thrives. With a strong commitment to employee development, you will have access to numerous growth opportunities, collaborative projects, and a supportive community that values inclusivity and excellence in education. Located in a dynamic city known for its rich culture and student-friendly atmosphere, this role as a Lecturer in Business Analytics promises not only professional fulfilment but also a rewarding lifestyle.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst in Sheffield
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Dunhillmedical.
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We think you need these skills to ace Data Analyst in Sheffield
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Dunhillmedical, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Dunhillmedical. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Dunhillmedical
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Dunhillmedical!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
