At a Glance
- Tasks: Design and maintain data models that drive insights and support decision-making.
- Company: Join the Law Society's innovative Data and AI team.
- Benefits: Enjoy hybrid working, flexible benefits, and career progression opportunities.
- Other info: Collaborate with talented colleagues in a culture of trust and respect.
- Why this job: Make a real impact with data while working in a supportive environment.
- Qualifications: Strong SQL skills and experience with Power BI or similar tools.
The predicted salary is between 40000 - 50000 £ per year.
Job Description
The Role Join the Law Society's Data and AI team at an exciting stage of our data transformation journey.
Having recently implemented our first enterprise Data Platform, we're looking for an Analytics Engineer to help shape the next phase of our data and analytics capability.
In this role, you will design, build and maintain trusted data models and analytics products that enable reporting, generate valuable insights and support informed decision-making across the organisation.
Working closely with data engineers, analysts and business stakeholders, you'll transform complex data into well-governed, reusable analytical models that power reporting tools such as Power BI.
You'll also play a key role in improving data quality, enhancing data accessibility and ensuring colleagues can confidently find, trust and use data to drive business outcomes.
This is an excellent opportunity to join a knowledgeable and growing Data and AI team where you'll have the chance to influence best practice, work with modern technologies and contribute to the continued evolution of our data platform.
What we're looking for We're looking for someone with a passion for data and analytics who can bridge technical expertise with business needs.
You will have: Strong SQL skills and experience designing reliable, scalable and maintainable data models, optimised for BI tools such as Power BI.
Experience developing reports, dashboards and semantic models using Power BI or similar analytics platforms.
Knowledge of modern cloud data technologies such as Databricks, Snowflake or Azure Data Factory.
An understanding of data governance, data lineage and data quality principles.
The ability to work collaboratively with stakeholders to translate business requirements into practical data solutions.
A proactive, collaborative approach with a commitment to continuous improvement.
Desirable skills include: Experience using Git and Python.
Experience working within Agile delivery environments.
Relevant cloud or data certifications.
What's in it for you This is an exciting opportunity to join a respected membership organisation with a strong reputation for excellence and legal expertise.
You'll work alongside talented colleagues who are passionate about using data to deliver meaningful impact across the organisation.
At the Law Society, we're committed to fostering an inclusive workplace where equality, diversity and inclusion are valued, and where our culture is built on trust, clarity, excellence and respect.
We offer: Hybrid working.
A generous and flexible benefits package.
A supportive and collaborative working environment.
Excellent opportunities for learning, development and career progression.
Please note: i f you are an internal applicant, Pay Policy will apply.
The Law Society represents solicitors in England and Wales.
From negotiating with and lobbying the profession's regulators, government and other decision makers, to offering training and advice, we're here to help, protect and promote solicitors.
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Analytics Engineer in London employer: The Law Society
The Law Society is an exceptional employer that prioritises employee development and a collaborative work culture, making it an ideal place for a Service Analyst to thrive. With a strong focus on delivering high-quality IT services, employees benefit from ongoing training opportunities and a supportive environment that encourages innovation and teamwork. Located in a vibrant area, the organisation offers a unique chance to contribute to meaningful work while enjoying a balanced professional life.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer in London
✨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 The Law Society!
✨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 Analytics Engineer at The Law Society.
✨Leverage Professional Networks
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 The Law Society.
✨Apply Directly through Our Website
When you find a suitable opening like Analytics Engineer at The Law Society, 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 Analytics Engineer in London
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 The Law Society, 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 The Law Society. 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 The Law Society
✨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 The Law Society!
✨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.
