At a Glance
- Tasks: Build analytics-ready datasets and develop transformation pipelines using SQL and PySpark.
- Company: Join a leading organisation in a major data transformation programme.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on high-quality data and career advancement.
- Why this job: Shape the future of data modelling and deliver impactful insights across the business.
- Qualifications: Experience as an Analytics Engineer with strong SQL and PySpark skills.
The predicted salary is between 50000 - 60000 £ per year.
We're partnering with a highly respected organisation undergoing a major data transformation, and they're looking for an Analytics Engineer to join their growing data team on a 12-month fixed-term contract.
This is a fantastic opportunity to work on a cutting-edge Lakehouse platform, helping shape how data is modelled, structured, and delivered across the business.
The Opportunity:
You'll sit at the heart of the data function, bridging the gap between engineering and business teams. Your work will directly enable high-quality reporting, trusted insights, and data-driven decision-making at scale.
What You'll Be Doing:
- Building curated, analytics-ready datasets using modern modelling techniques
- Developing robust transformation pipelines using SQL and PySpark
- Collaborating with Data Engineers to enhance the data platform
- Translating business needs into scalable, well-structured data models
- Embedding data quality, testing, and governance into workflows
- Working closely with BI teams and stakeholders to deliver reliable insights
What We're Looking For:
- Proven experience as an Analytics Engineer or similar role
- Strong SQL skills and experience with complex data transformations
- Hands-on experience with PySpark and modern data platforms (Lakehouse)
- Solid understanding of dimensional modelling
- Strong communication skills - able to work across technical and business teams
- A passion for clean, reliable, high-quality data
If you are interested please apply, to follow up please email or message me on LinkedIn.
Analytics Engineer - Lakehouse Data Pipelines (12-Month) employer: Energy Jobline ZR
Join a forward-thinking organisation in London that prioritises innovation and employee development. As an Analytics Engineer, you'll be part of a dynamic team driving a significant data transformation initiative, with access to competitive salaries, hybrid working arrangements, and opportunities for professional growth in a collaborative work culture. This role not only allows you to work on cutting-edge technology but also empowers you to make impactful contributions to data-driven decision-making across the business.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer - Lakehouse Data Pipelines (12-Month)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your SQL and PySpark projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common questions related to data modelling and transformation. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨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 Analytics Engineer - Lakehouse Data Pipelines (12-Month)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Analytics Engineer role. Highlight your SQL and PySpark expertise, and don’t forget to mention any experience with data transformation and modelling techniques.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data and how your background makes you a perfect fit for our team. Be sure to connect your experiences to the specific responsibilities mentioned in the job description.
Showcase Your Projects:If you've worked on relevant projects, whether in a professional setting or as personal endeavours, include them in your application. This gives us insight into your hands-on experience with data pipelines and analytics-ready datasets.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, it shows us you’re serious about joining our team!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss complex data transformations you've handled in the past and how you approached them. Practising some SQL queries can also help you feel more confident.
✨Familiarise Yourself with PySpark
Since this role involves working with PySpark, it’s crucial to have a solid understanding of its functionalities. Try to work on a small project or two using PySpark to demonstrate your hands-on experience during the interview.
✨Understand Dimensional Modelling
Get a good grasp of dimensional modelling concepts as they are key to the role. Be ready to explain how you’ve applied these techniques in previous projects and how they can benefit the organisation's data structure.
✨Communicate Effectively
Strong communication skills are essential for bridging the gap between technical and business teams. Practice explaining complex data concepts in simple terms, as you may need to do this during the interview to showcase your ability to collaborate effectively.
