Working hours: 35 hours per week, Monday to Friday
Duration: Permanent
Location: Gloucester
Job Ref: 203895

ABOUT US

Benefact Group is a unique international financial services Group made up of over 30 businesses. We are owned by a charity and have been the 3rd largest UK corporate donor over a decade, having given away £250 million since 2014. We have ambitious plans to become the UK’s number one corporate donor, with strategic objectives in place to double the Group’s size.
We believe it’s essential to attract, empower, grow and reward talented people, offering fantastic opportunities for career and personal development. Our giving ethos, 135-year history and the diversity of what we do, has enabled us to build a culture of kindness, great ambition, and of passionate people driven to do better and be better.
At Benefact Group, we are committed to creating an inclusive culture and building an environment where each and every one of us feels valued and respected. We are a community made up of people with a range of different backgrounds, abilities, perspectives, beliefs and interests and we value the strength this brings to us as a Group. We welcome applications from everyone.

IF YOU NEED ANY ADDITIONAL SUPPORT DURING THE RECRUITMENT PROCESS, THEN PLEASE LET US KNOW.

Directory of Social Change’s UK Guides to Company Giving 2017-2

ABOUT THE ROLE

Benefact Group, are looking for a Lead Data & Analytics Engineer to join our Gloucester office.
Within the role, you will lead the design, development, and optimisation of cloud-based data pipelines and analytics solutions using modern cloud technologies. This role involves ensuring scalable, secure, and efficient cloud data services that drive insights and knowledge across the organisation, while providing technical leadership and strategic direction.
Joining our rapidly expanding and innovative Group presents a fantastic opportunity to develop your career and become an integral part of an inclusive, purpose-led organisation.

KEY RESPONSIBILITIES

• Team Leadership & Management: Lead and manage a team of data engineers, providing guidance, mentorship, and support to ensure successful project delivery. Foster a collaborative and high-performance environment, encouraging continuous learning and professional development. Support the Head of Data Operations to coordinate team activities, set clear goals, and monitor progress to achieve project milestones and objectives.
• Cloud Data Engineering: Lead the design, build, and maintenance of cloud-native data pipelines using ETL/ELT, streaming, and modern data processing techniques.
• Data Visualisation & Analytics: Oversee the provision of scalable, cloud-based analytics and data services that empower business decision-making.
• Operational Support & Troubleshooting: Ensure high availability and reliability of cloud data solutions by providing second-line support and optimising performance.
• Cloud Governance & Security: Implement and enforce best practices for security, compliance, and governance in cloud data environments.
• Collaboration & Agile Development: Work closely with stakeholders, attending Data Analytics Board (DAB) meetings, and leading agile development processes.
• Data Strategy & Automation: Drive the creation of automated and self-service solutions, enabling Data as a Service for users while fostering a data-driven culture.
• Continuous Integration & Deployment: Lead the support of cloud-based CI/CD pipelines for data solutions, enabling efficient releases and updates.
• Technical Leadership: Mentor and support business users and citizen data scientists in adopting cloud-native analytics and data science tools.
• Hands-On Development: Actively participate in the design, coding, and testing of cloud-native data pipelines and analytics solutions.
• Technical Problem Solving: Engage in troubleshooting complex data issues and performance bottlenecks, providing hands-on solutions.
• Prototyping & Innovation: Lead the development of prototypes and proof-of-concept projects to explore new technologies and methodologies.
• Code Reviews & Best Practices: Conduct code reviews to ensure adherence to best practices and high-quality code standards.
• Tool & Technology Evaluation: Actively evaluate and implement new tools and technologies to enhance the data engineering and analytics capabilities.
• Data Integration: Directly manage and execute data integration tasks, ensuring seamless data flow across various systems and platforms.
• Performance Tuning: Perform hands-on performance tuning and optimisation of data pipelines and cloud resources.