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- Tasks: Lead a dynamic team to transform data engineering capabilities and drive innovation.
- Company: Join a forward-thinking organisation focused on data and AI excellence.
- Benefits: Competitive salary, career development, and a collaborative work environment.
- Other info: Opportunity for significant career growth and influence across the organisation.
- Why this job: Shape the future of data infrastructure and make a real impact in a fast-paced setting.
- Qualifications: Proven leadership in data engineering and expertise in cloud technologies.
The predicted salary is between 80000 - 100000 ÂŁ per year.
We are seeking a visionary, delivery‑focused Head of Data Engineering to lead the transformation of JD’s enterprise data engineering capabilities. Reporting to the Group Director of Data & AI, you will shape a modern, scalable, and secure data estate that accelerates analytics, AI, and digital innovation across the Group. You will lead a Data Engineering function of 15+ within the wider Data & AI organisation, shaping the strategic direction, capability, standards, and operational excellence of data engineering across the group and driving the evolution of our enterprise data engineering capabilities across our cloud and legacy environments. Your remit spans cloud platform engineering, pipeline automation, real‑time data processing, curation, and the enablement of business intelligence, data science and AI teams. You will set the vision for the future of our data infrastructure, ensuring scalability, resilience, security, commercial impact, and alignment to the Group’s strategic objectives. You will manage a highly skilled team of data engineers, while partnering with high‑level stakeholders across technology and business functions to ensure the data foundation unlocks measurable value.
Responsibilities
- Strategic Leadership & Vision
- Define and own the long‑term data engineering strategy and roadmap driving modernisation, standardisation, and cloud‑first best practices.
- Lead the migration away from legacy data systems into modern, scalable cloud platforms, ensuring scalability and cost‑optimised use of cloud services.
- Identify new technologies, patterns, and methodologies (e.g., streaming, ML/AI enablement, data lineage, orchestration) that advance our capabilities.
- Champion engineering excellence, governance, data quality, and enterprise‑grade reliability across all teams and pipelines.
- Leadership & People Development
- Lead, mentor, and develop a high‑performing team of data engineering professionals, setting clear expectations and fostering a culture of excellence, collaboration, and continuous improvement.
- Establish clear role pathways, skills development plans, and a culture of continuous improvement.
- Drive strong engineering culture, collaboration, and accountability across the team.
- Manage team capacity, resourcing, and prioritisation to meet business demand effectively.
- Platform & Engineering Delivery
- Oversee the design, build, and optimisation of cloud‑based data pipelines, datasets, and infrastructure supporting analytics, reporting, and AI products.
- Ensure data engineering teams deliver reliable and efficient pipelines for ingestion, transformation, enrichment, and curation of large‑scale data.
- Establish and enforce engineering standards across CI/CD, version control, data modelling, documentation, observability, and code quality.
- Ensure the creation of trusted, governed data models and consumption layers for downstream stakeholders.
- Stakeholder Collaboration & Influence
- Build trusted relationships with senior business leaders, acting as a strategic partner to help teams utilise data effectively and make informed decisions.
- Work with senior business stakeholders to understand priorities, ensuring data engineering directly enables commercial, operational, and strategic outcomes.
- Partner closely with Data Science, BI, Product, Cloud Infrastructure, Security, and Architecture teams to deliver integrated and scalable solutions.
- Communicate complex technical concepts clearly and frame engineering decisions in terms of business impact.
- Governance, Security & Compliance
- Ensure data platforms meet regulatory, security, and compliance requirements, including secure pipeline design, access control, and lineage.
- Embed good governance practices across metadata, cataloguing, quality, and monitoring.
- Define and maintain data engineering standards, documentation, and policies to ensure consistency, compliance, and long‑term maintainability.
Role Objectives & KPIs
- Deliver a scalable, modern, and cost‑efficient enterprise data platform.
- Reduce cloud spend and cost‑to‑serve through optimisation and engineering standards.
- Improve the reliability, performance, and availability of mission‑critical data pipelines.
- Increase data quality, consistency, and usability across priority domains.
- Strengthen engineering capability and maturity through talent development and best‑practice standard and frameworks.
- Improved productivity and engagement across Data Engineering teams.
- On‑time delivery of strategic data initiatives in support of analytics, AI, and digital transformation goals.
Skills and Experience
- Significant senior‑level experience in Data Engineering leadership roles (Head, Director, or equivalent) within fast‑paced, complex organisations.
- At least five years’ experience managing and developing high‑performing Data Engineering teams.
- Deep expertise in cloud data engineering within GCP, pipelines, orchestration, and distributed data processing.
- Strong background in SQL, Python, CI/CD, and software engineering best practices.
- Experience designing and scaling data platforms, data models, and ingestion frameworks across structured and unstructured sources.
- Understanding of ML/AI enablement, data curation strategies, and metadata/lineage tooling.
- Proven ability to drive organisational change, modernise technology stacks, and embed best practices.
- Proven ability to coach and mentor technical teams, raising capability and embedding high delivery standards.
- Skilled at simplifying complexity and embedding standards that balance technical rigour with business value and cost.
- Effective communicator who can influence and engage senior stakeholders across business and technology domains who can provide authoritative guidance.
- Experience in large‑scale, multi‑brand, or global enterprises; retail experience is advantageous.
- Demonstrated ability to learn and adopt new technologies, especially emerging AI capabilities.
- Strong leadership and people development skills to develop a growing team of data engineering professionals and foster the adoption of data‑driven decision‑making across the business.
Head of Data Engineering in Bury St Edmunds employer: JD GROUP
Contact Detail:
JD GROUP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering in Bury St Edmunds
✨Tip Number 1
Network like a pro! Get out there and connect with people in the data engineering field. Attend meetups, webinars, or industry events. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to cloud platforms, data pipelines, and AI. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with SQL, Python, and CI/CD practices. Also, think about how you can communicate complex concepts clearly to non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your leadership experience and how you can drive data engineering excellence in our organisation.
We think you need these skills to ace Head of Data Engineering in Bury St Edmunds
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the Head of Data Engineering role. Highlight your experience in cloud data engineering, team leadership, and any relevant technologies like SQL and Python. We want to see how your skills align with our vision!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how you can drive transformation at JD. Be sure to mention specific achievements that demonstrate your ability to lead and innovate.
Showcase Your Leadership Style: We’re looking for someone who can lead a high-performing team. In your application, give examples of how you've mentored others and fostered a culture of excellence. Let us know how you inspire collaboration and continuous improvement!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. We can’t wait to hear from you!
How to prepare for a job interview at JD GROUP
✨Know Your Data Engineering Stuff
Make sure you brush up on your data engineering knowledge, especially around cloud platforms like GCP. Be ready to discuss your experience with pipelines, orchestration, and distributed data processing. They’ll want to see that you can not only talk the talk but also walk the walk when it comes to modernising data systems.
✨Showcase Your Leadership Skills
As a Head of Data Engineering, you'll be leading a team, so it's crucial to demonstrate your leadership style. Prepare examples of how you've mentored teams, set clear expectations, and fostered a culture of excellence. Highlight any successful projects where your leadership made a difference.
✨Communicate Clearly with Stakeholders
You’ll need to build trusted relationships with senior business leaders, so practice explaining complex technical concepts in simple terms. Think about how you can frame your engineering decisions in terms of business impact, as this will resonate well with non-technical stakeholders.
✨Prepare for Governance and Compliance Questions
Given the importance of governance, security, and compliance in data engineering, be ready to discuss how you've ensured these aspects in your previous roles. Have examples ready that showcase your understanding of regulatory requirements and how you've implemented good governance practices.