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- Tasks: Design and maintain scalable data pipelines for renewable energy assets.
- Company: Leading renewable energy and digital solutions business with a focus on innovation.
- Benefits: Competitive salary, career growth, and the chance to work on impactful projects.
- Why this job: Make a real difference in renewable energy while developing your technical skills.
- Qualifications: Experience with APM platforms, strong Python and SQL skills required.
- Other info: Join a dynamic team with a strong engineering culture and long-term stability.
The predicted salary is between 36000 - 60000 £ per year.
An established renewable energy and digital solutions business is expanding its Asset Performance Management (APM) technology team and is hiring an experienced Data Engineer to support large-scale operational renewable assets. This role sits within a product-focused engineering group responsible for building and scaling data platforms used to monitor, optimise, and improve the performance of wind, solar, and energy storage assets globally. You will work closely with software engineers, data scientists, and platform teams to design and operate high-quality data pipelines that directly underpin operational decision-making and analytics for live energy assets.
Key responsibilities:
- Design, build, and maintain scalable data pipelines using Databricks (including Delta Live Tables).
- Develop robust ETL/ELT workflows ingesting data from operational, telemetry, and third-party systems.
- Optimise pipeline performance, reliability, and cost efficiency in cloud environments.
- Ensure data quality, lineage, governance, and documentation across production systems.
- Collaborate cross-functionally with analytics, product, and platform teams.
- Support CI/CD automation for data pipeline deployment.
- Contribute to reusable frameworks and engineering best practices within the team.
Essential experience:
Candidates must have prior, hands-on experience working with at least one of the following APM platforms: Power Factors, Bazefield, GPM. This experience is critical, as the role involves working directly with data models, integrations, and operational outputs from these platforms.
Technical requirements:
- Proven experience as a Data Engineer in production environments.
- Strong Python and SQL skills.
- Hands-on Databricks experience (DLT, Delta Lake; Unity Catalog desirable).
- Solid understanding of data modelling, data warehousing, and distributed systems.
- Experience with cloud data platforms (Azure preferred; AWS or GCP acceptable).
- Familiarity with Git-based workflows and CI/CD pipelines.
- Exposure to analytics or ML-driven use cases is beneficial.
Nice to have:
- Databricks certifications (Associate or Professional).
- Experience supporting asset-heavy or industrial environments.
- Background in energy, utilities, or infrastructure data platforms.
Why this role:
- Work on live, utility-scale renewable assets rather than abstract datasets.
- High-impact role within a mature but fast-evolving digital platform.
- Strong engineering culture with real ownership and technical influence.
- Long-term stability combined with ongoing platform growth and investment.
Senior Data Engineer in Slough employer: Piper Maddox
Contact Detail:
Piper Maddox Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in the renewable energy and data engineering space. Attend industry meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects, especially those using Databricks. This is your chance to demonstrate your hands-on experience and technical prowess, so make it shine!
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss your experience with APM platforms and how you’ve optimised data workflows in the past. Practice common interview questions and scenarios related to data engineering.
✨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 leg up in the hiring process. Let’s get you that Senior Data Engineer role!
We think you need these skills to ace Senior Data Engineer in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with APM platforms and data pipelines, as this will show us you’ve got the right skills for the job.
Showcase Your Projects: Include specific projects where you've designed or optimised data pipelines. We love seeing real-world examples of your work, especially if they relate to renewable energy or large-scale operations.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s relevant to the role. Make it easy for us to see your qualifications!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, we love seeing candidates who take that extra step.
How to prepare for a job interview at Piper Maddox
✨Know Your Data Inside Out
Make sure you’re well-versed in the data models and integrations from APM platforms like Power Factors or Bazefield. Brush up on your experience with Databricks, especially Delta Live Tables, as this will be crucial for the role.
✨Showcase Your Technical Skills
Be prepared to discuss your Python and SQL skills in detail. Have examples ready that demonstrate how you've built and optimised data pipelines in cloud environments, particularly Azure, as this is a key requirement.
✨Collaboration is Key
Highlight your experience working cross-functionally with software engineers and data scientists. Share specific instances where you’ve collaborated on projects to improve data quality or pipeline performance, as teamwork is essential in this role.
✨Prepare for Practical Scenarios
Expect to tackle practical scenarios during the interview. Think about how you would approach designing a scalable data pipeline or optimising an existing one. This will show your problem-solving skills and technical expertise.
