Highly attractive salary and benefits (shared openly at first conversation)
Working Type
Hybrid
Work Hours
37.5
Responsibilities
Lead the design, build and optimisation of robust, scalable data pipelines and platforms behind analytics, reporting, AI and machine learning
Qualifications
Ind Standard
Skills
Strong expertise across data engineering tooling & platforms: pipelines, cloud DS, SQL, Python, machine learning & AI driven analytics
Vitality HI - Emp Assistance Prog - Hols =30 days a year + BH - Prof development inc funded quals
Additional Benefits
CI cover - Excellent Pension scheme - Life assurance of six-times salary - Hybrid working
Region
West Yorkshire
Description
Border to Coast Pensions Partnership is one of the UK's largest pension pools and the largest asset manager outside London and Edinburgh. Owned by 18 Local Government Pension Scheme partner funds, we manage approximately £120 billion of assets on behalf of more than two million members.
As a customer-owned and customer-focused organisation, our purpose is to make a difference for the Local Government Pension Scheme. Integrity, collaboration and sustainability are at the heart of how we work, and we are continuing to invest in our technology, data and innovation capabilities to support our long-term strategic ambitions.
Our client is an FCA regulated asset manager with a reputation for taking the long view. Having built its success on disciplined, sustainable investment, the business is now making a significant commitment to the next generation of its data, analytics and AI capability, and this senior appointment sits at the centre of that programme.
You will lead the design, build and optimisation of the data pipelines and platforms on which the business will depend, setting the standard for data engineering across the organisation and ensuring that every solution satisfies the security, governance, quality and operational resilience expectations of a regulated environment.
What you will be doing
- Lead the design, build and optimisation of robust, scalable data pipelines and platforms behind analytics, reporting, AI and machine learning
- Set the standard for data engineering, architecture and best practice across the organisation
- Translate business and innovation requirements into effective technical solutions
- Ensure every solution meets security, data governance, quality and operational resilience requirements
- Evaluate and adopt new technologies where they add clear business value, from AI driven analytics and machine learning pipelines to modern cloud tooling and platform engineering
- Mentor other data engineers and grow the capability around you
- Build internal capacity across data architecture, data quality, storage and organisational assurance
- Embed a hybrid data strategy, with expertise sitting in operational functions and central senior support, assurance and guidance behind it
- Maintain the artefacts, technical documentation and operating procedures that keep knowledge shared and assured
- Develop and innovate data capabilities in line with the organisation's data strategy
- Partner with data management, risk, technology and business colleagues to keep data handling controlled and aligned to regulation
- Help business owners design and implement effective data compliance and controls across business systems
- Monitor platform performance and act on opportunities to improve
- Investigate and remediate data related problems through to resolution
- Identify and escalation risk across your area of responsibility
What you will need
- Strong expertise across data engineering tooling and platforms: pipelines, cloud data services, SQL and Python, with machine learning pipelines and AI driven analytics, built for reliability and scale
- A solid grounding in data governance, data quality, security and lineage within regulated or audit led environments
- A track record of designing solutions for regulatory reporting, management information and operational resilience
- Demonstrable success building and maintaining pipelines and platforms in demanding, complex business environments
- Fluency in SQL, Python and modern data engineering methods at enterprise level
- Time served supporting reporting, analytics, management information or operational data services
- Comfort working to defined data governance, security and quality standards
- An analytical, disciplined approach to complex data and control problems
- The confidence to manage stakeholders across technology, risk, architecture and the business
- Sound judgement when reconciling conflicting information and competing priorities
- Excellent written, verbal and numeracy skills, with high levels of integrity
- A degree or equivalent experience, with continued development in data engineering, data management, BI tools or data platform methodologies
It would also help if you have
- Financial services knowledge
- Experience of/in data architecture and data modelling
- Cyber security awareness, including ISO27001
- Previous data engineering within a financially regulated company
- Involvement in data strategies and data capability development
- Experience with Cloud based data services
- Exposure to AI, machine learning or advanced analytics workloads, including modern cloud tooling and platform engineering
- A history of mentoring or supporting other data professionals
- Certification in data engineering, cloud data services, data management, analytics, cyber security or a related technology discipline
- Broader corporate awareness spanning health and safety, ICT systems, information management and data protection