Description
Do you want to work to make Power for Good?We're the world's largest independent renewable energy company. We're guided by a simple yet powerful vision: to create a future where everyone has access to affordable, zero carbon energy.We know that achieving our ambitions would be impossible without our people. Because we're tackling some of the world's toughest problems, we need the very best people to help us. They're our most important asset so that's why we continually invest in them.RES is a family with a diverse workforce, and we are dedicated to the personal professional growth of our people, no matter what stage of their career they're at. We can promise you rewarding work which makes a real impact, the chance to learn from inspiring colleagues from across a growing, global network and opportunities to grow personally and professionally.Our competitive package offers a wide range of benefits and rewards.Job SummaryThe 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.AccountabilitiesKey accountabilities include but are not limited to:
1. 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.
2. Take ownership of engineering quality, automation, observability and optimise performance across the data and AI platform.
3. Implement robust engineering standards and lead delivery of and oversee curated datasets with strong data quality controls, lineage capture and monitoring into pipelines.
4. Engineer AI-ready data products that can safely be consumed through semantic models, APIs, SQL endpoints or AI tools.
5. Build the technical services required for AI-enabled consumption, including governed query patterns, meta data retrieval, logging and traceability.
6. Support API/MCP-style integration between AI and Fabric/Purview.
7. Ensure AI tools only consume approved, certified and access-controlled datasets.
8. Work with the platform, architect and governance leads to ensure secure identity, access, quality patterns, embed classification, certification, quality and audit into engineering.
SkillsThe successful candidate will need to demonstrate:
9. Advanced skills in Microsoft stack including Azure, Fabric, synapse, purview and AI engineering.
10. Expert in data and AI engineering delivery, tools and technologies including SQL, python and others.
11. Strong problem-solving skills, operational mindset and ability to mentor, train and QA data and AIengineers work.
12. Innovation in the latest technologies for best practice data and AI engineering.
13. 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.
14. Skilled in data and AI engineering for AI/ML initiatives.
Qualifications and Experience
15. Degree in a relevant field directly related to data and AI.
16. Significant experience delivering enterprise-grade data and AI engineering solutions in production environments and leading teams to deliver high performance outcomes.
17. 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.
18. Extensive experience of working with Data and AI teams that provide in-depth AI, analytics reporting capabilities across the business.
19. Hands on current technical data and AI engineering experience.
20. 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.
21. 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.
22. Leading and maintaining security and privacy by design: access controls, handling of PII, auditability.
23. Demonstrated ability to improve reliability, cost, performance and maintainability of data platforms.
24. 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.