At a Glance
- Tasks: Lead analytics engineering, transforming court data into high-quality products for analysis and modelling.
- Company: Join HMCTS, a forward-thinking organisation committed to justice and innovation.
- Benefits: Enjoy 25 days annual leave, flexible working, and a competitive pension scheme.
- Other info: Embrace a culture of diversity and continuous learning in a supportive environment.
- Why this job: Make a real impact in the justice system while leading a dynamic team.
- Qualifications: Experience in analytics engineering and strong skills in Azure, Python, and SQL required.
The predicted salary is between 55000 - 65000 € per year.
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.
Head of Analytics Engineering employer: Ministry of Justice
HMCTS is an exceptional employer that prioritises innovation and inclusivity within its analytics engineering team. With a strong commitment to employee development, flexible working arrangements, and a supportive culture, we empower our staff to excel in their roles while contributing to meaningful projects that enhance the justice system. Our competitive benefits package, including generous annual leave and a contributory pension scheme, further underscores our dedication to fostering a rewarding work environment.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Analytics Engineering
✨Tip Number 1
Network like a pro! Reach out to current or former employees at HMCTS on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by diving deep into analytics engineering trends. Brush up on your Azure, Python, and SQL skills, and be ready to discuss how you've tackled complex data challenges in the past.
✨Tip Number 3
Showcase your leadership skills! Be ready to share examples of how you've led teams, managed projects, and fostered an inclusive culture. HMCTS values strong leaders who can inspire and empower others.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're serious about joining the team at HMCTS.
We think you need these skills to ace Head of Analytics Engineering
Some tips for your application 🫡
Show Your Passion for Data:When you're writing your application, let your enthusiasm for analytics engineering shine through! We want to see how much you love transforming data into valuable insights and how you can lead our team in delivering top-notch data products.
Tailor Your Experience:Make sure to highlight your relevant experience in analytics-focused data engineering. We’re looking for specific examples of how you've designed analytical data models or led teams in delivering data products. The more tailored your application, the better!
Be Clear and Concise:We appreciate clarity! When explaining your skills and experiences, keep it straightforward and to the point. Use bullet points if necessary to make your application easy to read and digest. Remember, we want to understand your journey quickly!
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do – just follow the prompts!
How to prepare for a job interview at Ministry of Justice
✨Know Your Data Inside Out
As the Head of Analytics Engineering, you'll need to demonstrate a deep understanding of analytics-focused data engineering. Brush up on your knowledge of analytical data models and dimensional modelling techniques. Be ready to discuss how you've previously transformed complex datasets into high-quality data products.
✨Showcase Your Leadership Skills
This role requires strong leadership capabilities. Prepare examples of how you've led multidisciplinary teams and fostered an inclusive culture. Think about specific instances where you’ve empowered team members or resolved complex people issues, as this will resonate well with the interviewers.
✨Be Agile and Adaptable
Familiarise yourself with agile delivery methodologies, as they are crucial for this position. Be prepared to discuss how you've implemented agile practices in past roles, managed backlogs, and iterated based on user feedback. Highlight any experience you have with tools that support these methodologies.
✨Communicate Complex Concepts Simply
You'll often need to explain intricate data and technical concepts to non-technical audiences. Practice articulating your thoughts clearly and concisely. Consider preparing a few examples where you've successfully communicated complex ideas, ensuring you can convey your expertise without overwhelming your listeners.
