Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the design and implementation of scalable analytics data models for an Energy Intelligence Platform.
- Company: Join a forward-thinking company focused on innovative energy solutions.
- Benefits: Competitive daily rate, flexible remote work, and opportunities for professional growth.
- Other info: Work in a dynamic environment with a focus on data-driven culture and collaboration.
- Why this job: Shape the future of data practices and make a real impact in the energy sector.
- Qualifications: Expertise in dimensional data modelling, SQL, and strong communication skills.
Duration: Contract
Workload: Full time hours
Setup: Freelance (Daily rate / Limited Company / Umbrella / Sole Trader)
Location: Remote (UK‑based)
Overview
We need a Lead Analytics Engineer to define, scale and future‑proof data practices for a complex Energy Intelligence Platform operating at real‑time scale.
Key Responsibilities
- Act as the technical architect for scalable, reliable analytics data models built on modern best practices.
- Define and enforce analytics engineering standards across the data organisation, including CI/CD, testing and modular design.
- Design advanced dimensional data models to support highly complex analytical and operational scenarios.
- Own the long‑term vision for data modelling, quality and governance, including GDPR incident response.
- Partner closely with Product and senior stakeholders to translate business goals into clear, scalable technical solutions and shape the analytics roadmap.
- Champion a strong, data‑driven culture across cross‑functional teams.
Must‑Have Skills
- Mastery of dimensional data modelling and complex analytics engineering solutions.
- Expert‑level SQL with strong hands‑on experience using dbt.
- Proven ability to drive adoption of new standards, tools and patterns without direct authority.
- Exceptional communication and stakeholder management skills across technical and non‑technical audiences.
- Deep, end‑to‑end understanding of the data lifecycle from ingestion through to consumption.
Nice‑to‑Have
- Ownership of organisation‑wide data modelling or analytics engineering strategy.
- Experience designing and implementing data governance frameworks.
- Leading rapid proofs of concept for modern data tooling.
Lead Analytical Engineer employer: Airswift
Contact Detail:
Airswift Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Analytical Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry and let them know you're on the hunt for a Lead Analytical Engineer role. You never know who might have the inside scoop on an opportunity or can refer you directly.
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your mastery of dimensional data modelling and complex analytics solutions. Use real-world examples to demonstrate how you've driven adoption of new standards and tools in previous roles.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and dbt skills. Be ready to discuss your experience with CI/CD, testing, and modular design. We want to see how you can translate business goals into scalable technical solutions!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're serious about joining our team and contributing to a strong, data-driven culture.
We think you need these skills to ace Lead Analytical Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Analytical Engineer role. Highlight your experience with dimensional data modelling and analytics engineering solutions, as well as your SQL expertise. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Talk about your experience in defining analytics standards and your ability to communicate with both technical and non-technical audiences. We love a good story!
Showcase Your Projects: If you've worked on relevant projects, don’t hold back! Share examples that demonstrate your mastery of analytics engineering and your approach to data governance. We’re keen to see how you’ve tackled complex scenarios in the past.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Airswift
✨Know Your Data Models
Make sure you brush up on your knowledge of dimensional data modelling. Be ready to discuss how you've designed and implemented complex analytics solutions in the past. This will show that you can hit the ground running and understand the intricacies of the role.
✨Showcase Your SQL Skills
Since expert-level SQL is a must-have, prepare to demonstrate your hands-on experience with it. You might be asked to solve a problem or optimise a query during the interview, so practice some common SQL challenges beforehand.
✨Communicate Clearly
Exceptional communication is key, especially when dealing with both technical and non-technical stakeholders. Practice explaining complex concepts in simple terms. This will help you convey your ideas effectively and show that you can bridge the gap between teams.
✨Be Ready to Discuss Governance
Data governance is a big part of this role, so be prepared to talk about your experience with data quality and compliance, especially regarding GDPR. Share examples of how you've managed data governance frameworks in previous roles to demonstrate your expertise.