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 projects with a focus on innovation and collaboration.
- Why this job: Shape the future of data engineering and AI in a rapidly evolving field.
- Qualifications: Degree in relevant field and 3+ years of hands-on 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.
Data Engineer / AI Engineer employer: Avis Budget Group
Join our dynamic Operational Analytics team in Bracknell, where innovation meets opportunity. As a Data Engineer / AI Engineer, you'll thrive in a collaborative work culture that values creativity and initiative, with ample opportunities for professional growth and development. Enjoy the unique advantage of shaping cutting-edge data solutions while being part of a supportive environment that encourages continuous learning and embraces the latest technologies.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer / AI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and AI/ML. We want to see what you've built from scratch, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in data engineering and AI. We recommend practicing coding challenges and discussing your thought process clearly.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Engineer / AI Engineer
Some tips for your application 🫡
Show Off Your Skills:When you're writing your application, make sure to highlight your hands-on experience with data engineering. We want to see how you've built things from scratch, so don’t hold back on showcasing your Python and SQL prowess!
Be Clear and Concise:Keep your application clean and well-structured. Just like the code we love, your written application should be easy to read and understand. Use bullet points where necessary to make your achievements pop!
Tailor Your Application:Make sure to tailor your application to our job description. We’re looking for someone who can operate in ambiguity and has a 'zero-to-one' mindset, so reflect that in your writing. Show us you get what we're about!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Avis Budget Group
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and SQL. Brush up on your experience with cloud platforms like Snowflake or AWS, and be ready to discuss how you've used them in past projects.
✨Showcase Your Building Skills
Prepare examples of data models or ETL/ELT pipelines you've built from scratch. Be specific about the challenges you faced and how you overcame them. This will demonstrate your hands-on experience and 'zero-to-one' mindset.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You’ll need to engage with business stakeholders, so being able to translate their needs into technical solutions is key. Think of scenarios where you’ve done this before.
✨Stay Curious About AI/ML
Since the role involves integrating AI capabilities, show your enthusiasm for AI/ML concepts. Discuss any relevant projects or ideas you have for implementing AI features in data workflows. This will highlight your proactive approach and passion for the field.
