At a Glance
- Tasks: Build and optimise large-scale data pipelines using cutting-edge technologies.
- Company: Join a market-leading tech business at the forefront of smart housing innovation.
- Benefits: Salary up to £71,000, 10% bonus, 33 days holiday, and pension.
- Other info: Collaborative team environment with excellent career progression opportunities.
- Why this job: Accelerate your career while working on exciting AI and Machine Learning projects.
- Qualifications: Strong Python, SQL, and PySpark skills; experience in data engineering.
The predicted salary is between 60000 - 71000 £ per year.
Data Engineer Bristol | Hybrid (3 Days Onsite) Salary Benefits – £60,000 to £71,000 10% bonus, 33 days holiday, pension, health Career Progression Modern Tech Stack Pyspark | ML | AI | Databricks | Kafka | AWS
Are you a Data Engineer with strong Python, SQL and PySpark skills who is looking for the opportunity to step up and accelerate your career? We're partnering with a market-leading technology business that is investing heavily in its data platform and is at the forefront of innovation within the smart housing sector. Processing billions of sensor readings every month, they're looking for a talented Data Engineer to join their growing team and help build the next generation of scalable data solutions.
This opportunity is ideally suited to a mid-level Data Engineer who is ready to take on more responsibility, work on complex technical challenges, and gain exposure to cutting-edge technologies including Databricks, Kafka, Streaming, AI and Machine Learning.
The Opportunity
- Build and optimise large-scale data pipelines
- Work with billions of data points generated from IoT devices
- Develop solutions using Python, SQL and PySpark
- Gain exposure to Databricks, Kafka and streaming technologies
- Contribute to Machine Learning and AI initiatives
- Work alongside Data Scientists and Software Engineers
- Influence architecture and engineering best practices
- Play a key role in exciting greenfield projects
What We’re Looking For
- Strong commercial experience as a Data Engineer
- Advanced Python and SQL skills
- Strong PySpark experience
- Experience building and maintaining scalable data pipelines
- Understanding of data modelling and database design principles
- Strong analytical and problem-solving capabilities
- Excellent communication and stakeholder engagement skills
- Degree in Computer Science, Mathematics, Statistics or a related discipline would be advantageous
Desirable Skills
- Experience with any of the following would be beneficial but not essential:
- Databricks
- Apache Kafka
- Real-time streaming technologies
- AWS services
- ClickHouse
- Infrastructure as Code
- CI/CD practices
Why Join?
This is more than just another Data Engineer role. It's an opportunity to join a business that genuinely invests in technology, learning and innovation. If you're looking for a company where you can progress into a senior position, develop expertise in modern big data technologies, and work on exciting AI and Machine Learning projects, this could be the perfect next step. If you're an ambitious Data Engineer with strong Python, SQL and PySpark skills and you're ready to take your career to the next level, we'd love to hear from you.
Data Engineer | Learn Kafka & Databricks | Big Data Technologies | 10% Bonus employer: Opus Recruitment Solutions
Opus Recruitment Solutions is an excellent employer, offering a dynamic and inclusive work culture that prioritises employee growth and development. With opportunities to work on high-profile projects across major UK cities, employees benefit from a hybrid working model that promotes work-life balance while engaging in meaningful work that makes a difference. The company values innovation and collaboration, ensuring that every team member can contribute to creating accessible and scalable solutions.
Contact Details:
Opus Recruitment Solutions Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer | Learn Kafka & Databricks | Big Data Technologies | 10% 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 Opus Recruitment Solutions!
✨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 Data Engineer | Learn Kafka & Databricks | Big Data Technologies | 10% Bonus at Opus Recruitment Solutions.
✨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 Opus Recruitment Solutions.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer | Learn Kafka & Databricks | Big Data Technologies | 10% Bonus at Opus Recruitment Solutions, 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 Data Engineer | Learn Kafka & Databricks | Big Data Technologies | 10% 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 Opus Recruitment Solutions, 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 Opus Recruitment Solutions. 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 Opus Recruitment Solutions
✨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 Opus Recruitment Solutions!
✨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.
