Role Purpose
The Head of Data Engineering & Analytics provides strategic and operational leadership for the organisation’s data platforms, data engineering capability, and analytical services.
The role exists to ensure that:
- Data is reliable, well-governed, and fit for business use
- Analytics and reporting are aligned to business strategy
- The data function operates as a coherent system rather than a collection of tools or projects
The role balances:
- Technical authority
- Delivery oversight
- Stakeholder leadership
in order to maximise the value of data across the organisation.
Scope and Impact
The role:
- Leads the design and evolution of the data platform and analytical architecture
- Sets direction for how data is acquired, structured, governed, and consumed
- Ensures that data engineering and analytics activities support strategic objectives
- Influences senior stakeholders on the effective use of data
The Head of Data Engineering & Analytics operates with:
- Broad autonomy within agreed strategy
- Responsibility for shaping standards and ways of working
- Accountability for technical and delivery outcomes
Key Responsibilities (SFIA-8 Aligned)
Strategy and Direction
(SFIA: IT Strategy & Planning, Information Strategy)
- Define and maintain the vision and roadmap for data engineering and analytics
- Ensure alignment between business strategy and data capability
- Identify future capability needs and develop plans to address them
- Balance short-term delivery with long-term sustainability
Architecture and Data Foundations
(SFIA: Solution Architecture, Data Management)
- Own the overall data architecture, including:
- Data models
- Integration patterns
- Analytical layers
- Ensure consistency across domains and regions
- Promote reuse and modular design over bespoke solutions
- Act as design authority for significant data initiatives
Delivery and Operational Oversight
(SFIA: Programme & Project Management, Service Management)
- Ensure that data products (pipelines, datasets, reports) are delivered:
- Predictably
- Securely
- To an agreed quality bar
- Establish and maintain a clear delivery operating model
- Monitor delivery risks, dependencies, and capacity
- Support prioritisation and sequencing of work
Standards, Governance and Quality
(SFIA: Governance, Quality Management, Information Security)
- Define and uphold standards for:
- Data modelling
- Engineering practices
- Analytics development
- Ensure compliance with organisational policies and regulatory obligations
- Promote strong data quality, lineage, and traceability
- Embed governance as an enabling function, not a barrier
Stakeholder Leadership
(SFIA: Stakeholder Relationship Management)
- Build trusted relationships with senior stakeholders
- Translate business needs into data and analytics solutions
- Communicate progress, risks, and outcomes clearly
- Promote a culture of transparency and shared ownership
Capability and People Leadership
(SFIA: Learning & Development Management, People Management)
- Develop and support the data engineering and analytics community
- Promote coaching, mentoring, and skills development
- Foster collaboration across technical and business teams
- Create an environment of accountability, learning, and continuous improvement
Ways of Working
The Head of Data Engineering & Analytics:
- Operates at enterprise level rather than project level
- Focuses on building systems and capability, not just delivering outputs
- Encourages reuse, standardisation, and automation
- Ensures that knowledge is captured and shared
- Reduces reliance on heroics through strong foundations and process
Skills and Experience
Technical and Analytical
- Deep understanding of:
- Data engineering
- Data warehousing and modelling
- Analytical and reporting platforms
- Experience designing and governing complex data estates
- Strong grasp of data quality, lineage, and security principles
Strategic and Organisational
- Ability to:
- Translate strategy into execution
- Manage competing priorities
- Make informed trade-offs
- Work with ambiguity
Interpersonal and Leadership
- Credible at senior stakeholder level
- Able to influence without relying solely on authority
- Communicates clearly to technical and non-technical audiences
- Builds alignment across diverse groups
Success Measures
The role will be considered successful when:
- Data pipelines are stable and trusted
- Analytical outputs are aligned with business priorities
- Reuse and modularity increase
- Delivery becomes more predictable
- Stakeholder confidence in data improves
- Governance is embedded without slowing progress
SFIA 8 Alignment (Indicative)
Primary SFIA skills at Level 5 include:
- IT Strategy & Planning
- Information Strategy
- Solution Architecture
- Data Management
- Governance
- Stakeholder Relationship Management
- Programme & Project Management
- Learning & Development Management
What You Bring…
✅ Strategic Data Leadership
- Experience leading cross-functional teams across engineering, reporting, governance, and analytics.
- Demonstrated ability to influence and align senior stakeholders across business units.
- Clear understanding of how data enables confident decisions and operational success.
✅ Trusted Reporting & Assurance Thinking
- Expertise in building reconciled, validated reports that explain and withstand scrutiny.
- Strong understanding of headcount, financial, and project metrics across the data lifecycle.
- Ability to explain pipeline logic, identify mismatches, and trace root causes.
✅ Engineering Fluency & Metadata Design
- Proficient in SQL, data pipeline orchestration, and metadata-driven engineering approaches.
- Experience implementing data catalogue, lineage, and quality control tools.
- Familiarity with Lakehouse architecture, semantic models, and cloud-native data services.
✅ Modern Analytics & AI Governance
- Knowledge of deploying AI tools for insight and anomaly detection.
- Understanding of explainability, validation, and responsible use of machine learning.
- Experience introducing new technologies into a BAU environment with confidence and control.
✅ Enablement & Delivery Culture
- Passionate about improving team maturity through reusability, clarity, and autonomy.
- Effective communicator, able to guide others with clarity and technical integrity.
- Collaborative mindset with strong internal publishing, mentoring, and uplift behaviours.