Head of Data & Engineering

Cardiff
1 year ago
Applications closed

Related Jobs

View all jobs

Head of Data Science

Head Of Data Science

Head of Research Data Services, Global Data Sciences, Oncology Therapy Area, Research and Devel[...]

Chief Data Scientist & Commercial Strategy Leader

Senior Data Science Manager

Data Engineer (Data Science)

Leading Transportation organisation are seeking to hire a Head of Data & Engineering in this newly created role. You will lead a team of developers and analysts to provide a robust data platform on their journey to self-serve information, providing insight and analysis with the sole purpose of providing excellent service to customers. Outside of Data Engineering you will fulfil a broad remit across, Data Architecture, Security and Data Quality Management

Client Details

Leading Transportation organisation

Description

Leading Transportation organisation are seeking to hire a Head of Data & Engineering in this newly created role. You will lead a team of developers and analysts to provide a robust data platform on their journey to self-serve information, providing insight and analysis with the sole purpose of providing excellent service to customers. Outside of Data Engineering you will fulfil a broad remit across, Data Architecture, Data Security and Data Quality Management.

Dimensions of the role:

Deliver a wide range of projects with internal and external suppliers and have autonomy over an annual budget of £1M - £2M.
Projects will typically consist of contributing to 3-7 smaller projects and 1 - 2 larger projects.
Manage a team of 3 staff with the scope to hire additional headcount in 2025
Strategy & Planning, typically annually and up to 3 years in advance.

Key Responsibilities:

Lead and manage the Data Engineering team, by providing strategic direction, and fostering a high-performing and collaborative working environment to ensure alignment with business goals, foster innovation and enhance productivity.
Develop and implement a robust data engineering strategy that aligns with the IT and Digital Services Strategy and Data Strategy by providing alignment with business objectives, engagement with key stakeholders, assessment of the current data landscape, defining clear objectives, and developing a data governance framework, to ensure a robust data engineering strategy that aligns with business goals
Overseeing the development, implementation and management of a robust data platform ecosystem to leverage the power of data and AI initiatives by setting measurable goals such as; reducing operational costs, increasing data accessibility and by designing and building a scalable and flexible Azure Cloud environment
Support ETL common data structure and business intelligence architectures by designing and implementing ETL processes, establishing common data structures, and developing business intelligence architectures to provide improved data quality and consistency and operational efficiency
Champion the adoption of data-driven decision-making across the organisation by securing leadership buy-in, articulating a clear vision and setoff measurable goals for the adoption of data driven practices, and through training and education, to ensure significant improvements in efficiency, customer satisfaction, and overall organisational performance.
Lead on the build of a data community through the creation of cross functional working, shared platforms and data stewardship where communities of data engineers and analysts work together on stable, accurate and assured data sets to improve decisions and performance.
Foster a culture of service excellence and continuous improvement within the team by developing and implementing training programs to ensure the team has the skills and knowledge to deliver high-quality services.
Lead the development and execution of a data governance framework by defining its objectives and scope, establishing a governance structure, developing policies and standards, and implementing data management processes to ensure data quality, regulatory compliance, data security, operational efficiency and strategic decision making.
Oversee the implementation and integration of big data technologies and tools, including a focus on optimising performance and efficiency for AI workloads by selecting relevant technologies and tools, designing and implementing data pipelines, and ensuring data quality and governance, to enhance the quality and usability of data to also foster a culture of innovation
Lead on performance improvements by collaborating with IT and Digital Services Team senior team to identify data-driven solutions to business challenges

Profile

Key Skills and Experience:

Degree in Data Science, Computer Science, Information Technology, or a related field.
Significant experience of developing and delivering data strategies.
Demonstrable experience in leading and managing data platform development and operations within a large organisation.
In-depth knowledge of data platform technologies, including Azure data warehouses, data lakes, and data governance tools.
Knowledge of optimising data pipelines, pipeline architectures and integrated datasets.
Demonstrable knowledge of working with and understanding data architecture principles and best practice.
Experience of procuring and implementing cloud-based data management solutions.
Experience of implementing data security and compliance frameworks.
Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
Experience of leading a team and providing solutions to data challenges.
Experience with scripting languages (e.g., Python, SQL)Job Offer

Opportunity to work on a major Data Transformation Programme

Opportunity to drive Data Strategy, Platforms and Growth

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

Neurodiversity in AI Careers: Turning Different Thinking into a Superpower

The AI industry moves quickly, breaks rules & rewards people who see the world differently. That makes it a natural home for many neurodivergent people – including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a career in artificial intelligence, you might have been told your brain is “too much”, “too scattered” or “too different” for a technical field. In reality, many of the strengths that come with ADHD, autism & dyslexia map beautifully onto AI work – from spotting patterns in data to creative problem-solving & deep focus. This guide is written for AI job seekers in the UK. We’ll explore: What neurodiversity means in an AI context How ADHD, autism & dyslexia strengths match specific AI roles Practical workplace adjustments you can ask for under UK law How to talk about your neurodivergence during applications & interviews By the end, you’ll have a clearer picture of where you might thrive in AI – & how to set yourself up for success.