At a Glance
- Tasks: Own and optimise Power BI models, ensuring high-performance reporting and metric governance.
- Company: Dynamic analytics firm with a focus on innovation and collaboration.
- Benefits: Excellent salary, hybrid work model, and opportunities for professional growth.
- Other info: Exciting role with potential for career advancement in a thriving tech environment.
- Why this job: Join a cutting-edge team and elevate your skills in data analytics and reporting.
- Qualifications: Experience with Power BI, DAX, and SQL; strong communication skills required.
The predicted salary is between 49500 - 60500 £ per year.
Do you take pride in razor sharp metric accuracy and high performance reporting estates? We are working with a long term partner to find an Analytics Engineer to act as the central authority for their Power BI ecosystem. Operating in a hub-and-spoke analytics model, you will bridge domain analysts and data engineering, elevating raw insights into enterprise grade, productionised reporting.
What You'll Do
- Own the Gold Layer: Build and optimize high-performance Power BI semantic models and star-schema architectures within a Unified, AI-powered analytics platform.
- Productionize Reports: Review, refine, and promote reports from domain workspaces (Finance, Financial Crime, Marketing) into central production.
- Drive Metric Governance: Establish and enforce a company-wide KPI glossary, ensuring total consistency in business metrics.
- Maximize Performance & Security: Master DAX optimization, implement deployment pipelines, and configure row-level security (RLS).
What You Bring
- Significant hands on experience productionising Power BI reports and managing live estates.
- Deep expertise in DAX, dimensional modelling (star schema), and layered data architectures.
- Demonstrable excellence with SQL.
- Exposure to Microsoft Fabric, Azure Synapse, or Azure Data Factory.
- High technical rigor and diplomatic communication.
- You catch the discrepancies others miss and naturally elevate the team's standards.
BI Developer / Finance Analytics Engineer in Reading employer: Datatech Analytics
Datatech Analytics is an exceptional employer located in the vibrant City of London, offering a dynamic work culture that fosters collaboration and innovation. As a Trading Operations Graduate Analyst, you will benefit from comprehensive training and mentorship, ensuring your professional growth while working alongside industry experts in a fast-paced environment. With a commitment to employee well-being and a focus on meaningful contributions to global trading operations, Datatech Analytics provides a rewarding career path for ambitious graduates.
StudySmarter Expert Advice🤫
We think this is how you could land BI Developer / Finance Analytics Engineer in Reading
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Datatech Analytics!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like BI Developer / Finance Analytics Engineer at Datatech Analytics.
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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 Datatech Analytics.
✨Apply Directly through Our Website
When you find a suitable opening like BI Developer / Finance Analytics Engineer at Datatech Analytics, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace BI Developer / Finance Analytics Engineer in Reading
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 Datatech Analytics, 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 Datatech Analytics. 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 Datatech Analytics
✨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 Datatech Analytics!
✨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.
