The Head of Analytics Engineering leads the function responsible for transforming extracted court and tribunal data into trusted, high-quality data products. These data products are used by analysts, modellers, machine learning engineers, management information reporting teams and approved external users to support operational delivery, performance improvement and strategic decision‑making across HMCTS and the Ministry of Justice.
The role provides technical and delivery leadership for analytics‑focused data engineering. It ensures that analytical datasets are well modelled, quality assured, reusable and clearly documented. The role plays a critical part in enabling HMCTS to make confident use of its data.
HMCTS Digital and Technology Services (DTS) own the ingestion of data onto the Strategic Data Platform. This role begins once data has been extracted and focuses on curation, transformation and analytical usability.
The role sits within the Data Team within the HMCTS Strategy and Analysis Directorate and works closely with reporting, modelling, data management, data platforms, data quality and digital colleagues. It requires a strong balance of technical expertise, leadership capability and the ability to work collaboratively across organisational boundaries.
Success in the role is demonstrated through consistent use and reuse of a suite of analytical data products covering a wide range of HMCTS services, reduced duplication of effort, and increased trust in HMCTS data. It also includes the responsible adoption of new tools and techniques, such as AI, where they demonstrably improve quality, efficiency or analytical capability.
The post‑holder will represent HMCTS in cross‑justice data initiatives, working with MoJ, CPS, Probation, Police and external partners to strengthen analytical data interoperability, promote shared standards, and support sector‑wide insight.
This line management role provides senior strategic people leadership and direction aligned with HMCTS and Civil Service priorities. It shapes workforce strategy and drives capability development and performance in line with Civil Service Line Management Standards and Ministry of Justice Values, championing wellbeing and a culture of fairness, inclusion, and recognition.
The role will report into the HMCTS Deputy Director, Data.
Leadership and direction
Lead and develop the Analytics Engineering function, setting a clear direction for analytics‑focused data engineering across HMCTS.
Build a culture of quality, collaboration and continuous improvement.
Lead innovation in analytics engineering, ensuring the team explores and adopts new tools and capabilities, including AI and emerging platform features, in a way that improves quality, efficiency and reuse.
Lead the development and adoption of shared analytics engineering standards, building collective ownership and consistency across the team.
Act as the senior technical leader and head of profession for analytics engineering in HMCTS.
Lead the adoption and embedding of agile delivery methodologies within the analytics engineering team, shaping ways of working that support iterative delivery, clear prioritisation and continuous user feedback.
Provide consistent leadership to your area of the business and define and implement objectives, aligned with HMCTS and Civil Service priorities.
Identify trends and remove performance barriers and make strategic people decisions.
Promote an inclusive culture that supports diversity and creates a safe working environment that delivers the organisation’s objectives
Data product delivery
Own the delivery of analytical data products used by analysts, modellers, machine learning engineers, management information teams and approved researchers.
Ensure analytical datasets are:
Built to meet HMCTS wide data standards, principles and definitions.
Fit for analytical, MI and machine learning use.
Well modelled, consistent, documented and governed through agreed data contracts.
Reusable for internal and external requirements.
Balance service specific requirements with cross HMCTS standards.
Engineering standards and quality
Set and enforce standards for:
Data modelling.
Transformation logic.
Testing and validation.
Version control and release management.
Ensure data quality checks are embedded within analytical datasets.
Define, implement and enforce the use of data contracts to clearly specify the structure, quality, timeliness and ownership expectations for analytical data products, working with Digital and Technology Services and data producers.
Act as the primary interface with the Machine Learning Operations (MLOps) function, ensuring that analytics engineering provides stable, well governed and model ready datasets to support safe model deployment and monitoring.
Agree and maintain clear hand‑offs with MLOps covering dataset versioning, schema change management, data quality thresholds and escalation routes where data contract breaches risk model performance.
Work closely with Data Quality, Data Governance and Data Management colleagues to align on definitions, reference data and quality expectations.
Delivery and prioritisation
The postholder will collaborate with the Data Project Management Office to plan, sequence and track analytics engineering work, manage dependencies, and provide clear visibility of delivery progress, risks and capacity constraints.
Prioritise analytics engineering work in line with:
HMCTS and Data Team agreed annual plans and day-to-day priorities.
Dependencies on data ingestion and platform availability.
Manage delivery risks and dependencies proactively.
Ensure changes to data products are controlled and clearly communicated to users before release.
Balance competing priorities to optimise performance supporting the talent pipeline in your area of the business.
Collaboration and stakeholder engagement
Work closely with Reporting and Analysis, Modelling and Forecasting, and priority programmes.
Collaborate with Digital and Technology Services where changes affect analytical datasets, without owning ingestion or platform delivery.
Contribute to governance and prioritisation discussions where analytical data products are impacted.
Represent HMCTS in cross-justice data transformation programmes, working with MoJ Data Directorate, CPS, HMPPS, Home Office, Police Digital Service and other justice partners to align analytical data models, quality standards and AI readiness.
This is a senior technical leadership role. The postholder is expected to set direction, standards and assurance for analytics engineering across HMCTS rather than undertake routine day‑to‑day coding.
Essential
Capability aligned to the Government Digital and Data Profession Capability Framework for Head of Analytics Engineering.
Significant experience in analytics engineering or analytics‑focused data engineering, delivering data products for analysis, modelling and management information.
Strong expertise in designing analytical data models, use of dimensional modelling techniques and structuring data to support reuse, performance reporting and advanced analytics.
Proven experience setting, maintaining and assuring technical standards across analytics engineering teams, rather than relying on individual delivery.
Strong practical expertise in the Microsoft Azure data and analytics technology stack, advanced experience using Python for data transformation and analytical workflows and strong SQL skills for querying, transforming and validating large analytical datasets.
Experience using GitHub (or equivalent) for version control, peer review and collaborative development within analytics or data engineering teams.
Strong understanding of data quality, testing, validation and controlled release practices.
Experience leading and developing multidisciplinary technical teams, including capability development and performance management.
Ability to explain complex data and technical concepts clearly to non‑technical audiences.
Experience working in complex organisational environments with multiple stakeholders and competing priorities.
Strategic leadership and people management skills to coach and empower managers to resolve complex people issues and build high performing teams.
Desirable
Experience delivering data products using agile delivery methodologies, including working in multidisciplinary teams, managing backlogs and iterating based on user needs.
Experience designing or working with data contracts, or similar mechanisms to manage expectations between data producers and consumers.
Experience working with large and complex operational or administrative datasets.
Familiarity with data governance, master data and reference data concepts.
The role requires significant judgement in managing competing and often conflicting demands for analytical data products from across HMCTS and the wider Ministry of Justice. The postholder must actively manage stakeholder expectations, balancing urgent operational requests with longer term strategic priorities and agreed delivery plans.
The Analytics Engineering function routinely faces demand that exceeds available capacity. The postholder is therefore responsible for making clear, evidence‑based prioritisation decisions, transparently communicating trade‑offs and ensuring that limited resource is deployed where it delivers the greatest organisational value.
The role requires careful management of dependencies on Digital and Technology Services delivery timescales, including data ingestion and platform changes. The postholder must anticipate and manage delivery risks arising from these dependencies, adjusting plans and priorities where necessary and escalating issues appropriately.
The role will often require resolving tensions between short‑term, high‑profile requests and the need to invest in sustainable data products, standards and technical debt reduction. Decisions must consider impacts on service delivery, analytical quality, user trust and longer‑term maintainability.
The postholder is expected to take a proactive approach, using agile delivery principles to sequence work, respond to emerging needs and continuously reassess priorities, while maintaining alignment with agreed standards, governance and strategic objectives.
The role has direct line management responsibility for 4 G7 Lead Data Engineers and is responsible for a wider team of 8 Senior Data Engineers and 4 HEO Data Engineers within the Analytics Engineering function.
The postholder will be responsible for workforce planning, training plans for capability development and performance management across this function. This includes ensuring the team has the right skills and capacity to meet current and future demand.
The role manages delivery within agreed budgets and resource constraints, ensuring value for money and effective use of specialist skills.
The postholder will support the Deputy Director to manage a circa £1 million budget for contractor resources, including the commissioning of specialist capability where required. This includes the creation, management and approval of deliverables in statements of work, ensuring that supplier outputs meet agreed standards, timelines and quality expectations.
The role also provides expert support to negotiate and secure analytics engineering resources for data product delivery within new and existing HMCTS programmes, working with programme teams to shape realistic delivery plans and align funding with analytical priorities.
The Head of Analytics Engineering operates with a high degree of autonomy within agreed HMCTS strategic, governance and financial frameworks.
The postholder is the HMCTS senior authority on analytics engineering. They are expected to set direction, make authoritative decisions on analytics engineering standards, approaches and priorities, and act as the final escalation point for technical and delivery issues relating to analytical data products.
The postholder has discretion to determine how analytics engineering capacity is deployed, including the authority to defer, sequence or decline work where requests are not aligned with agreed priorities, standards or available capacity. This includes making difficult trade offs between short term demands and longer term investments in sustainable data products and technical foundations.
The postholder is expected to exercise professional judgement in managing dependencies with Digital and Technology Services, programmes and external suppliers, escalating risks where required but resolving issues independently wherever possible.
Decisions taken in this role have a material impact on the quality, reliability and credibility of HMCTS analytical data and are expected to be taken with confidence, transparency and accountability.
This role operates at the centre of HMCTS’s analytical, digital and delivery landscape. The postholder is expected to build and maintain strong relationships that enable the effective planning, prioritisation and delivery of analytical data products across services and programmes. These relationships are critical to aligning technical standards, managing dependencies, and ensuring that analytics engineering input supports HMCTS strategic objectives.
The post will report to the HMCTS Deputy Director, Data but maintain key relationships with the Deputy Directors for Performance and Reporting and Research Insight and Analysis.
The post holder should maintain good collaborative working relationships with their peers including the HMCTS Heads of Performance Reporting and Analysis, Data Management and Engineering, Data Quality, Data Strategy and Project Delivery, Data Access and Governance, Modelling, Research Insight, Evaluation and Forecasting.
It will be vital for the post-holder to develop and maintain excellent working relationships with Digital and Technology Services colleagues to ensure that the Data Team can access the data and documentation they need to develop quality data products.
Build strong working relationships with Ministry of Justice Data Directorate and Analysis colleagues, including analytics engineers, data engineers, statisticians, economists and operational researchers, to align analytical data products, share standards and patterns, and support cross‑justice analysis and insight.
Collaborate with wider data, digital and analytical leads across the Justice family, other governance departments, and approved external users engaged in justice sector data use.
Work with service and programme leads across HMCTS, to understand business priorities, shape analytical data product requirements, agree delivery expectations and ensure that analytics engineering input is planned, prioritised and aligned with wider service outcomes.
Governance forums where analytical data products are discussed, to provide authoritative advice on analytics engineering standards, data quality, delivery risks and trade‑offs, and to support informed decision‑making on priorities, investment and risk management.