At a Glance
- Tasks: Lead data modelling and engineering oversight for impactful analytics and AI projects.
- Company: Fast-growing London consultancy blending management consulting, data science, and software engineering.
- Benefits: Competitive salary up to £80k plus bonus, with opportunities for mentorship and growth.
- Other info: Dynamic environment with opportunities to mentor and influence engineering standards.
- Why this job: Join a high-impact team and shape the future of data engineering in a scaling consultancy.
- Qualifications: 5+ years in data engineering with experience in dbt, Airflow, and cloud technologies.
The predicted salary is between 70000 - 80000 £ per year.
A fast‑growing London consultancy blending management consulting, data science, and software engineering is hiring a Senior Data Engineer to join their small but high‑impact data team. You’ll work across major analytics and AI programmes for clients in retail, financial services, public sector, SaaS, and private equity.
What You’ll Do
- Lead data modelling, ETL/ELT pipelines, database design and backend components
- Provide technical steering and day‑to‑day engineering oversight
- Mentor junior and mid‑level engineers
- Shape engineering standards in a consultancy that’s still scaling its data practice
What They’re Looking For
- 5+ years in data/analytics engineering
- Experience with dbt, Airflow, and cloud warehouses
- Exposure to AWS/Azure/GCP and IaC
Senior Data Engineer – Central London | Up to £80k + bonus employer: Oliver Bernard
Join a dynamic and innovative consultancy in Central London that values collaboration and creativity, offering a vibrant work culture where your contributions directly impact major analytics and AI programmes. With competitive salaries, performance bonuses, and ample opportunities for professional growth, this company is dedicated to nurturing talent and fostering an environment where you can thrive alongside a passionate team of experts.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer – Central London | Up to £80k + bonus
✨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 Oliver Bernard!
✨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 Senior Data Engineer – Central London | Up to £80k + bonus at Oliver Bernard.
✨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 Oliver Bernard.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer – Central London | Up to £80k + bonus at Oliver Bernard, 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 Senior Data Engineer – Central London | Up to £80k + bonus
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 Oliver Bernard, 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 Oliver Bernard. 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 Oliver Bernard
✨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 Oliver Bernard!
✨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.
