At a Glance
- Tasks: Build scalable data pipelines and support machine learning workflows using Python and Scala.
- Company: Join Capgemini, a global leader in tech transformation and innovation.
- Benefits: Enjoy hybrid working, extensive training, and wellbeing support.
- Why this job: Make a real impact by delivering data solutions that drive business decisions.
- Qualifications: Strong skills in Python, Scala, and big data frameworks required.
- Other info: Be part of a diverse team committed to ethical practices and sustainability.
The predicted salary is between 28800 - 48000 £ per year.
We are seeking a Data Engineer with strong proficiency in Python and Scala to support predictive modeling, statistical analysis, and data-driven product initiatives. This role focuses on preparing high-quality datasets, enabling machine-learning workflows, and building scalable pipelines using modern data-engineering tools. You will work closely with engineering, product, and business teams to deliver reliable, production-ready data solutions across cloud environments.
Hybrid working: The places that you work from day to day will vary according to your role, your needs, and those of the business; it will be a blend of Company offices, client sites, and your home; noting that you will be unable to work at home 100% of the time.
Your Role:
- Perform data cleaning, transformation, and feature engineering to support ML and analytics use cases.
- Build and optimize data pipelines and automated workflows using Python, Scala, PySpark, and relevant ML libraries.
- Develop and maintain scalable data-processing systems for both batch and real-time workloads.
- Support model development by collaborating with data scientists and translating requirements into engineering solutions.
- Partner with cross-functional teams to deliver insights and ensure seamless data availability for decision-making.
Your Skills:
- Strong expertise in Python and Scala, with hands-on experience in Pandas, NumPy, Scikit-learn, PySpark, and MLlib.
- Solid SQL skills and experience working with large-scale, big-data frameworks (e.g., Spark, Hadoop).
- Familiarity with major cloud platforms such as Azure, AWS, or GCP.
- Ability to build scalable pipelines, automate workflows, and optimize data-engineering processes.
- Excellent analytical and problem-solving skills, with the ability to interpret and communicate complex findings clearly.
We are a Disability Confident Employer: Capgemini is proud to be a Disability Confident Employer (Level 2) under the UK Government's Disability Confident scheme. As part of our commitment to inclusive recruitment, we will offer an interview to all candidates who declare they have a disability and meet the minimum essential criteria for the role. Please opt in during the application process.
Make It Real (what does it mean for you): You'd be joining an accredited Great Place to work for Wellbeing in 2024. Employee wellbeing is vitally important to us as an organisation. We see a healthy and happy workforce as a critical component for us to achieve our organisational ambitions. To help support wellbeing we have trained 'Mental Health Champions' across each of our business areas, and we have invested in wellbeing apps such as Thrive and Peppy.
You will be empowered to explore, innovate, and progress. You will benefit from Capgemini's 'learning for life' mindset, meaning you will have countless training and development opportunities from thinktanks to hackathons, and access to 250,000 courses with numerous external certifications from AWS, Microsoft, Harvard ManageMentor, Cybersecurity qualifications and much more.
You will be joining one of the World’s Most Ethical Companies®, as recognised by Ethisphere® for 13 consecutive years. We live our values by making ethical business choices every day. Working ethically is at the centre of our culture at Capgemini, meaning you will be helping to create a future we can all be proud of.
Why you should consider Capgemini: Growing clients' businesses while building a more sustainable, more inclusive future is a tough ask. When you join Capgemini, you'll join a thriving company and become part of a collective of free-thinkers, entrepreneurs and industry experts. We find new ways technology can help us reimagine what's possible. It's why, together, we seek out opportunities that will transform the world's leading businesses, and it's how you'll gain the experiences and connections you need to shape your future. By learning from each other every day, sharing knowledge, and always pushing yourself to do better, you'll build the skills you want. You'll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making the world a better place rarely is.
About Capgemini: Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organisations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Data Engineer (Python - Scala) employer: Capgemini
Contact Detail:
Capgemini Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Python - Scala)
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python and Scala. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions. Get comfortable explaining your thought process and how you tackle problems—this is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Engineer (Python - Scala)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and Scala, as well as any relevant big data frameworks. We want to see how your skills align with the role, so don’t be shy about showcasing your projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our team. Keep it concise but impactful – we love a good story!
Showcase Your Problem-Solving Skills: In your application, mention specific examples where you've tackled complex data challenges. We’re keen on seeing how you approach problem-solving, especially in collaborative settings with cross-functional teams.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It’s the best way for us to receive your application and ensure it gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Capgemini
✨Know Your Tech Stack
Make sure you brush up on your Python and Scala skills, especially with libraries like Pandas, NumPy, and PySpark. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data problems. Think about times when you had to clean or transform datasets for machine learning or analytics, and be ready to explain your thought process and the impact of your solutions.
✨Understand the Business Context
Familiarise yourself with the company’s goals and how data engineering supports their initiatives. Be prepared to discuss how your work can contribute to predictive modelling and data-driven decisions, showing that you understand the bigger picture.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the tools they use, and the projects you'll be working on. This not only shows your interest but also helps you gauge if the company culture aligns with your values and career aspirations.