At a Glance
- Tasks: Design and develop Power BI dashboards for finance and wealth stakeholders.
- Company: Join a leading firm in the finance and asset management sector.
- Benefits: Competitive pay, flexible contract, and potential for extension.
- Other info: Opportunity to work with cutting-edge data tools and grow your career.
- Why this job: Make an impact by delivering critical reporting solutions in a fast-paced environment.
- Qualifications: Strong Power BI skills and experience in finance required.
The predicted salary is between 50000 - 65000 £ per year.
We are seeking an experienced Power BI Engineer to support our client's Wealth team. This is a critical hire to ensure continuity of reporting deliverables ahead of key deadlines.
Key Responsibilities:
- Design, develop, and maintain Power BI dashboards and reports for finance/wealth stakeholders.
- Translate business requirements into data models and visual insights.
- Support data validation, quality checks, and performance optimisation.
- Manage and enhance existing reporting solutions during transition period.
Must Have:
- Strong experience with Power BI (development, DAX, data modelling).
- Proven experience in Finance domain.
- Ability to deliver under tight deadlines and fast-paced environments.
- Experience working with stakeholders and translating business needs into reports.
- Solid understanding of data integration and reporting best practices.
Nice to Have:
- Experience with SQL / data warehousing.
- Knowledge of Azure data tools (e.g., Azure SQL, Data Factory, Synapse).
- Familiarity with agile delivery environments.
Skills: Power BI, Financial Management, Data Validation, Data Modeling, SQL, Azure Data Factory, Azure SQL Database.
Power BI engineer with Financial/ Wealth/Asset management domain exp (Associate Data Architect I) employer: UST
As a Principal Data Engineer at our company, you will thrive in a dynamic and innovative work culture that prioritises technical excellence and continuous learning. With opportunities for mentorship and collaboration across diverse teams, you will play a pivotal role in shaping the future of our cloud-scale data platform while enjoying the flexibility of a hybrid work environment in Nottingham or London. We are committed to fostering your professional growth and providing a supportive atmosphere where your contributions directly impact our success.
StudySmarter Expert Advice🤫
We think this is how you could land Power BI engineer with Financial/ Wealth/Asset management domain exp (Associate Data Architect I)
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like UST before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like UST.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like UST.
We think you need these skills to ace Power BI engineer with Financial/ Wealth/Asset management domain exp (Associate Data Architect I)
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at UST, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to UST, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab UST’s attention and show the tangible impact of your work.
How to prepare for a job interview at UST
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at UST.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at UST.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at UST.
