{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “Head of Analytics Engineering”, “description”: “
Overview
The Head of Analytics Engineering will lead the analytics‑engineering function within HMCTS, transforming court and tribunal data into trusted, high‑quality data products. The role delivers technical and delivery leadership for analytics‑focused data engineering, ensuring analytical datasets are well‑modelled, quality assured, reusable, and clearly documented.
Responsibilities
- Lead and develop the Analytics Engineering function, setting a clear direction for analytics‑focused data engineering across HMCTS.
- Own the delivery of analytical data products used by analysts, modellers, machine learning engineers, management information teams and approved researchers.
- Lead innovation in analytics engineering, ensuring the team explores and adopts new tools and capabilities, including AI and emerging platform features, to improve 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.
- Define, implement and enforce the use of data contracts to clearly specify the structure, quality, timeliness and ownership expectations for data used for analytical data products, working with Digital and Technology Services and data producers.
- Act as the primary interface for machine learning and data science, ensuring that analytics engineering provides stable, well‑governed and model‑ready datasets to support safe model deployment and monitoring.
- Provide consistent leadership to your area of the business and define and implement objectives, aligned with HMCTS and Civil Service priorities.
- Identify trends, remove performance barriers and make strategic people decisions.
- Promote an inclusive culture that supports diversity and creates a safe working environment.
Qualifications (Essential)
- 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, 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 Skills
- Knowledge of the justice system and the work of HMCTS.
- 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.
Behaviours
- Changing & Improving
- Leadership
- Working Together
- Delivering at Pace
Working Pattern & Travel
Minimum working hours are 30 hours over 4 days a week. Occasionally travel may be required to HMCTS sites to support project delivery.
Benefits
- Annual leave: 25 days on appointment, increasing to 30 days after five years’ service.
- Highly competitive contributory pension scheme.
- Training and development opportunities.
- Employee support networks and inclusive workplace culture.
- Flexible working policy and family‑friendly benefits.
EEO Statement
The Ministry of Justice is an inclusive employer committed to diversity and equal opportunities. All staff are entitled to equal treatment and reasonable adjustments will be made during the recruitment process where needed.
#J-18808-Ljbffr”, “datePosted”: “2026-05-20”, “hiringOrganization”: { “@type”: “Organization”, “name”: “Ministry of Justice”, “sameAs”: “https://uk.whatjobs.com/pub_api__cpl__436773648__4861?utm_campaign=publisher&utm_medium=api&utm_source=4861&geoID=33051” }, “jobLocation”: { “@type”: “Place”, “address”: { “@type”: “PostalAddress”, “addressLocality”: “City of Westminster” } } }Company: Ministry of Justice
Location: City of Westminster
Job Description:
Overview
The Head of Analytics Engineering will lead the analytics‑engineering function within HMCTS, transforming court and tribunal data into trusted, high‑quality data products. The role delivers technical and delivery leadership for analytics‑focused data engineering, ensuring analytical datasets are well‑modelled, quality assured, reusable, and clearly documented.
Responsibilities
- Lead and develop the Analytics Engineering function, setting a clear direction for analytics‑focused data engineering across HMCTS.
- Own the delivery of analytical data products used by analysts, modellers, machine learning engineers, management information teams and approved researchers.
- Lead innovation in analytics engineering, ensuring the team explores and adopts new tools and capabilities, including AI and emerging platform features, to improve 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.
- Define, implement and enforce the use of data contracts to clearly specify the structure, quality, timeliness and ownership expectations for data used for analytical data products, working with Digital and Technology Services and data producers.
- Act as the primary interface for machine learning and data science, ensuring that analytics engineering provides stable, well‑governed and model‑ready datasets to support safe model deployment and monitoring.
- Provide consistent leadership to your area of the business and define and implement objectives, aligned with HMCTS and Civil Service priorities.
- Identify trends, remove performance barriers and make strategic people decisions.
- Promote an inclusive culture that supports diversity and creates a safe working environment.
Qualifications (Essential)
- 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, 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 Skills
- Knowledge of the justice system and the work of HMCTS.
- 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.
Behaviours
- Changing & Improving
- Leadership
- Working Together
- Delivering at Pace
Working Pattern & Travel
Minimum working hours are 30 hours over 4 days a week. Occasionally travel may be required to HMCTS sites to support project delivery.
Benefits
- Annual leave: 25 days on appointment, increasing to 30 days after five years’ service.
- Highly competitive contributory pension scheme.
- Training and development opportunities.
- Employee support networks and inclusive workplace culture.
- Flexible working policy and family‑friendly benefits.
EEO Statement
The Ministry of Justice is an inclusive employer committed to diversity and equal opportunities. All staff are entitled to equal treatment and reasonable adjustments will be made during the recruitment process where needed.
#J-18808-Ljbffr…
Posted: May 20th, 2026