At a Glance
- Tasks: Build and optimise data pipelines and AI products for a sustainable future.
- Company: Join the world's largest independent renewable energy company.
- Benefits: Competitive salary, diverse benefits, and a focus on work-life balance.
- Other info: Diverse and inclusive workplace that values different perspectives.
- Why this job: Make a real impact in renewable energy through innovative data solutions.
- Qualifications: Degree in data/AI and experience in enterprise-grade solutions required.
The predicted salary is between 60000 - 80000 £ per year.
We’re the world’s largest independent renewable energy company, guided by a vision to create a future where everyone has access to affordable, zero‑carbon energy. Our competitive package offers a wide range of benefits and rewards.
The Senior Data and AI Engineer role is a unique opportunity to help build a world‑class global data and AI platform. You’ll be responsible for building production‑grade data pipelines and AI‑ready data products across Fabric, Azure and the legacy estate, including the governed technical integration between AI tools and the enterprise data platform.
Accountabilities- Architect, build, implement and operate reliable, secure and observable data pipelines and curated datasets across the legacy and future platform.
- Deliver robust bronze, silver and gold data layers.
- Take ownership of engineering quality, automation, observability and optimise performance across the data and AI platform.
- Implement robust engineering standards and lead delivery of and oversee curated datasets with strong data quality controls, lineage capture and monitoring into pipelines.
- Engineer AI‑ready data products that can safely be consumed through semantic models, APIs, SQL endpoints or AI tools.
- Build the technical services required for AI‑enabled consumption, including governed query patterns, meta data retrieval, logging and traceability.
- Support API/MCP‑style integration between AI and Fabric/Purview.
- Ensure AI tools only consume approved, certified and access‑controlled datasets.
- Work with the platform, architect and governance leads to ensure secure identity, access, quality patterns, embed classification, certification, quality and audit into engineering.
- Advanced skills in Microsoft stack including Azure, Fabric, Synapse, Purview and AI engineering.
- Expert in data and AI engineering delivery, tools and technologies including SQL, Python and others.
- Strong problem‑solving skills, operational mindset and ability to mentor, train and QA data and AI engineers’ work.
- Innovation in the latest technologies for best practice data and AI engineering.
- Strong, clear communication and stakeholder management and reporting of risk, change and impact.
- The ability to thrive in this role which demands technical and data‑driven results.
- Skilled in data and AI engineering for AI/ML initiatives.
- Degree in a relevant field directly related to data and AI.
- Significant experience delivering enterprise‑grade data and AI engineering solutions in production environments and leading teams to deliver high performance outcomes.
- Proven experience as a Senior Data and AI Engineer, with a strong portfolio of building real‑time data and AI systems and teams using modern approaches.
- Extensive experience of working with Data and AI teams that provide in‑depth AI, analytics reporting capabilities across the business.
- Hands on current technical data and AI engineering experience.
- Extensive experience with Python including open‑source data libraries and frameworks and messaging systems, along with proficiency in building out modern data and AI warehouses.
- Azure data and AI mastery: Deep expertise in the Azure Ecosystem, specifically Azure Data Factory (ADF), Synapse, Unity Catalogue, Fabric, Purview: data lakes/lakehouse, data quality and testing frameworks and automation.
- Leading and maintaining security and privacy by design: access controls, handling of PII, auditability.
- Demonstrated ability to improve reliability, cost, performance and maintainability of data platforms.
- Building quality global datasets for BI, AI and analytics consumption from many ingestion sources and leading/coaching and setting guardrails for regional data/analytics engineers and advising on projects.
At RES we celebrate difference as we know it makes our company a great place to work. Encouraging applicants with different backgrounds, ideas and points of view, we create teams who work together to solve complex problems and design practical solutions for our clients.
Senior Data and AI Engineer employer: RES
At RES, we pride ourselves on being the world's largest independent renewable energy company, dedicated to creating a sustainable future through affordable, zero-carbon energy. Our vibrant work culture fosters innovation and collaboration, providing employees with extensive growth opportunities in data and AI engineering while enjoying a competitive benefits package. Join us in a dynamic environment where diverse perspectives are celebrated, and your contributions will directly impact the global transition to renewable energy.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data and AI Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like RES!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data and AI Engineer at RES.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like RES.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data and AI Engineer at RES, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data and AI Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at RES, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RES. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RES
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at RES!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
