At a Glance
- Tasks: Analyse and present data using SQL and Power BI for a major system transition.
- Company: Join a forward-thinking university committed to innovation and transformation.
- Benefits: Flexible working hours, professional development opportunities, and a supportive team environment.
- Other info: Exciting opportunity for growth in a dynamic educational setting.
- Why this job: Be at the forefront of a significant data migration project that shapes the future of education.
- Qualifications: Experience with SQL and Power BI, plus strong analytical skills.
The predicted salary is between 29700 - 36300 £ per year.
The Data Analyst will play a key role in supporting the University's transition from legacy systems to Banner SaaS as part of the Student Record System (SRS) Transformation Programme. Working within the Data Architecture and Data Migration workstreams, you will use SQL, Power BI and reporting tools to query, analyse and present data to business stakeholders, enabling data validation, cleansing and informed decision-making ahead of migration and go-live activities.
Data Analyst: SQL & Power BI for Data Migration employer: University of East London
The University of East London is an exceptional employer, offering a dynamic work environment at the vibrant Docklands Campus. With a strong focus on employee growth and development, staff benefit from flexible working arrangements, a competitive salary, and generous perks such as a 20% pension contribution and subsidised gym membership, making it an ideal place for those seeking meaningful and rewarding careers in education.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst: SQL & Power BI for Data Migration
✨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 University of East London.
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We think you need these skills to ace Data Analyst: SQL & Power BI for Data Migration
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 University of East London, 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 University of East London. 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 University of East London
✨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 University of East London!
✨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.
