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- Tasks: Design and build robust data pipelines for real-time analytics in the energy sector.
- Company: Leading UK energy trading firm at the forefront of innovation.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Join a passionate team shaping the future of energy through data-driven insights.
- Qualifications: Strong skills in SQL, Python, and experience with Apache Spark and Airflow.
- Other info: Flexible working environment with a focus on performance and scalability.
The predicted salary is between 68000 - 102000 £ per year.
My client, an energy leader at the forefront of the UK market, is searching for a Data Engineer to join them as soon as possible. This is an exciting opportunity to join a highly experienced data and trading team helping to shape the future of energy through data-driven insight and technology.
We are looking for a Data Engineer who is passionate about building scalable, high-performance data systems using open-source technologies. You will play a key role in developing robust pipelines, optimising performance, and supporting real-time analytics across the business. This will be a hybrid role - ideally twice a week in London, but there is flexibility.
What you’ll be doing:
- Designing and building robust data ingestion pipelines
- Creating and optimising ETL / ELT processes across varied data volumes
- Developing data models and schemas to support analytics and product use cases
- Monitoring, troubleshooting and improving pipeline performance and reliability
- Implementing data quality, validation and monitoring processes
- Contributing to architecture decisions and the data roadmap
What we’re looking for:
- A strong engineer who cares about performance, scalability and clean design.
Key experience:
- Strong SQL and Python skills (pandas, NumPy, Spark)
- Hands-on experience with Apache Spark, Kafka, and Airflow
- Solid understanding of data warehousing and distributed computing
- Experience with Docker, Kubernetes, and CI/CD pipelines
- A problem-solving mindset and the ability to communicate complex ideas clearly
Data Engineer (Python + Airflow) employer: Norton Blake
Contact Detail:
Norton Blake Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Python + Airflow)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, Airflow, and data pipelines. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and common data engineering questions. Practice explaining your thought process clearly, as communication is key in this role.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Data Engineer (Python + Airflow)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Airflow, and any relevant data engineering projects. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
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 Technical Skills: Don’t forget to mention your hands-on experience with tools like Apache Spark, Kafka, and Docker. We’re looking for someone who can hit the ground running, so let us know what you’ve worked on!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at Norton Blake
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python, Airflow, and SQL. Brush up on your knowledge of Apache Spark and Kafka too, as these are crucial for the role. Being able to discuss your hands-on experience with these tools will show that you're not just familiar but also capable.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use the STAR method (Situation, Task, Action, Result) to structure your answers. This will demonstrate your analytical thinking and problem-solving mindset, which is key for a Data Engineer.
✨Understand Data Pipelines
Be ready to talk about your experience designing and building data ingestion pipelines. Discuss any ETL/ELT processes you've optimised and how you ensure data quality and reliability. This shows that you understand the core responsibilities of the role and can contribute from day one.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data architecture and future projects. This not only shows your interest in the role but also gives you insight into how you can fit into their team. Questions about their approach to real-time analytics or data quality processes can spark engaging conversations.