At a Glance
- Tasks: Design and build data infrastructure, develop AI features, and create scalable data pipelines.
- Company: Join a forward-thinking team in a dynamic analytics environment.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Exciting chance to work with cutting-edge technologies and make a real impact.
- Why this job: Shape the future of data engineering and AI in a rapidly evolving field.
- Qualifications: Degree in Computer Science or related field, with 3+ years of data engineering experience.
The predicted salary is between 60000 - 80000 £ per year.
As a Data Engineer / AI Engineer in the Operational Analytics team, you will be the hands-on builder who designs, develops, and maintains our data infrastructure from the ground up — ahead of full IT handover. This is not a Database Administrator role. We need someone who has built things from scratch, is comfortable operating in ambiguity, and is excited to shape both the engineering and AI layer of a growing analytics function.
What You'll Be Doing
- Write clean, well-documented Python and SQL code with a focus on performance, maintainability, and reusability.
- Architect and develop data models within our centralized data platform, ensuring data quality, consistency, and traceability.
- Build new data assets from raw sources, bridging operational systems and the analytical layer until IT takes full ownership.
- Develop and implement AI/ML-enabled data features — including data enrichment, anomaly detection, and predictive pipelines.
- Integrate AI APIs and LLM-based tools into data workflows to accelerate analytics at scale.
- Work closely with analysts and business stakeholders to understand data needs and translate them into robust engineering solutions.
- Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and serve data across the organization.
- Support the transition of built solutions to IT once production-ready, ensuring proper documentation and handover.
What You'll Bring
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering or a related field.
- 3+ years of hands-on experience in data engineering, strong managing large datasets and fluent with SQL querying, including building ETL/ELT pipelines and data models from scratch.
- Strong proficiency in Python (pandas, PySpark, or similar) and SQL.
- Experience with cloud-based data platforms (e.g., Snowflake, Azure DL, AWS S3, Databricks).
- Practical knowledge of AI/ML concepts and experience integrating AI capabilities into data products or pipelines.
- Excellent communication skills: able to engage with business stakeholders and translate requirements into technical designs.
- Comfortable working as a builder and owner before IT infrastructure is fully in place — a 'zero-to-one' mindset.
Nice to Have
- Familiarity with orchestration tools such as Apache Airflow, dbt, or Azure Data Factory.
- Exposure to LLM frameworks (LangChain, OpenAI API, Azure OpenAI).
- Experience with version control (Git/GitHub) and CI/CD practices for data pipelines.
Bracknell, Bracknell Forest, United Kingdom
Data Engineer / AI Engineer in Bracknell employer: Avis Budget Group
Join our dynamic team in Bracknell as a Data Engineer / AI Engineer, where you'll have the opportunity to shape the future of our data infrastructure and analytics function. We pride ourselves on fostering a collaborative work culture that encourages innovation and personal growth, offering comprehensive training and development programmes to help you advance your career. With a focus on cutting-edge technology and a commitment to employee well-being, we provide a stimulating environment that empowers you to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer / AI Engineer in Bracknell
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We think you need these skills to ace Data Engineer / AI Engineer in Bracknell
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!
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Craft a Tailored Cover Letter:For a full-time role at Avis Budget Group, 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 Avis Budget Group. 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 Avis Budget Group
✨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!
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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
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✨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.
