At a Glance
- Tasks: Lead the Analytics Engineering function and design high-quality data models.
- Company: A large, innovative organisation investing in their enterprise data platform.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on mentorship and technical leadership.
- Why this job: Join a pivotal Lakehouse programme and influence data governance across the organisation.
- Qualifications: Strong experience in analytics engineering, SQL, and PySpark.
The predicted salary is between 78000 - 78000 £ per year.
This is a rare opportunity to take a lead role in a growing Analytics Engineering function at a pivotal moment in its evolution. You will play a central part in a major Lakehouse programme, combining deep technical ownership with the chance to influence how data is modelled, governed and consumed across the organisation.
The Company
They are a large, complex organisation making continued investment in their enterprise data platform. Analytics sits at the heart of decision-making, with a clear mandate to expand engineering capability and mature the Lakehouse environment. The team is collaborative, technically ambitious and growing, with strong links across Engineering, BI and the wider business. This role sits within a well-established analytics function that is scaling its engineering remit.
The Role
- Take ownership of the curated or Gold layer within a Lakehouse architecture
- Design and deliver high-quality, analytics-ready data models that support trusted reporting
- Translate complex business requirements into robust SQL and PySpark transformation pipelines
- Shape how data is structured, modelled and served across multiple domains
- Embed data quality, testing, reliability and performance standards into pipelines
- Contribute to CI/CD and modern engineering best practices within the data platform
- Act as a technical mentor, supporting and guiding other Analytics Engineers
- Work closely with Data Engineers, BI teams and business stakeholders to deliver impact
Your Skills & Experience
- Strong commercial experience as an Analytics Engineer operating in a modern data platform
- Advanced data modelling capability, including dimensional and semantic modelling
- Strong PySpark development experience within a Lakehouse environment
- Advanced SQL skills for complex transformations
- Hands-on experience with Databricks, including pipelines and governance tooling
- A strong engineering mindset, with a focus on reliability, testing and maintainability
- Proven ability to mentor others and provide technical leadership
- Comfortable operating at the intersection of business and engineering
Lead Analytics Engineer, Lakehouse & Data Quality (12m FTC) employer: Energy Jobline ZR
As a leading employer in the analytics space, this large organisation offers a dynamic and collaborative work culture that prioritises innovation and technical excellence. Employees benefit from a strong focus on professional growth, with opportunities to lead impactful projects within a cutting-edge Lakehouse environment. The hybrid working model in London further enhances work-life balance, making it an attractive place for those seeking meaningful and rewarding careers in data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Analytics Engineer, Lakehouse & Data Quality (12m FTC)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best work, especially any projects related to data modelling or analytics. This will give you an edge and demonstrate your capabilities beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with SQL, PySpark, and data governance. Practising common interview questions can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Lead Analytics Engineer, Lakehouse & Data Quality (12m FTC)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your advanced data modelling capabilities and PySpark experience, as these are key for us at StudySmarter.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about analytics engineering. Share specific examples of how you've contributed to data quality and governance in previous roles, as this will resonate with our team.
Showcase Your Technical Skills:When detailing your experience, focus on your SQL and PySpark projects. We want to see how you've designed and delivered analytics-ready data models, so don't hold back on the details!
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’re considered for this exciting opportunity in our growing Analytics Engineering function.
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Lakehouse Inside Out
Make sure you understand the Lakehouse architecture and how it integrates with data modelling. Brush up on your knowledge of SQL and PySpark, as you'll likely be asked to demonstrate your skills in these areas during the interview.
✨Showcase Your Data Quality Mindset
Be prepared to discuss how you ensure data quality and reliability in your work. Think of specific examples where you've embedded testing and performance standards into your pipelines, as this will resonate well with the interviewers.
✨Demonstrate Your Mentorship Skills
Since the role involves mentoring other Analytics Engineers, come ready with examples of how you've supported and guided others in previous positions. Highlight your leadership style and how you foster collaboration within a team.
✨Connect Business Needs with Technical Solutions
The ability to translate complex business requirements into technical solutions is key. Prepare to discuss past experiences where you've successfully bridged the gap between business stakeholders and engineering teams, showcasing your communication skills.
