Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Principal Data Engineer

Mott MacDonald
City of London
1 week ago
Create job alert

Join to apply for the Principal Data Engineer role at Mott MacDonald.


Mott MacDonald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices.


Location: London, GB
Recruiter contact: Nikki George


About The Role

We’re looking for a Principal Data Engineer to play a leading role in shaping and implementing our enterprise data architecture. This position is ideal for someone who combines deep technical expertise with strong stakeholder engagement skills and a strategic mindset. You’ll help define and implement the data foundations that enable impactful AI and analytics solutions across our global engineering, consulting, and infrastructure business.


You’ll work closely with cross‑disciplinary teams, including data scientists, domain experts, and product managers, to design scalable, secure, and interoperable data systems. You’ll also help establish our enterprise data ontology and lead a small team of data engineers to turn that vision into reality.


What You’ll Do

  • Enterprise data pipeline design & optimisation: Design and implement robust data pipelines to map both structured and unstructured data from diverse sources into the enterprise vector store, ensuring high‑quality embeddings for downstream retrieval and analysis.
  • Ontology and data modelling: Lead the development of semantic data models and domain ontologies to enable data interoperability and traceability across the enterprise.
  • Team leadership: Provide technical direction and mentoring for a small team of data engineers, supporting their growth while maintaining delivery velocity.
  • Hands‑On engineering: Build, evolve, and maintain scalable, secure data pipelines, APIs, and infrastructure in a modern cloud environment (Azure preferred).
  • Stakeholder collaboration: Partner with technical and non‑technical stakeholders across business units to gather requirements, align roadmaps, and communicate architecture decisions effectively.
  • Governance & best practices: Promote robust data management, including lineage, observability, access control, and compliance with ethical data use.
  • Innovation & standards: Stay ahead of industry trends in data architecture, engineering, and metadata/semantic technologies—and bring them into practice where they add value.
  • Enterprise data architecture: Collaborate with other architects to define and implement data architecture patterns across systems and domains to support analytical, AI, and operational use cases.

What You’ll Bring

  • Excellent communication and stakeholder engagement skills—able to bridge technical detail and strategic business value.
  • Experience in data engineering and architecture, ideally in complex or regulated enterprise environments.
  • Expertise in designing and implementing scalable data architectures using cloud platforms (Azure preferred).
  • Strong experience with data modelling—from conceptual to logical and physical—and familiarity with data catalogues, knowledge graphs, or ontology tools.
  • Proven experience managing or mentoring other data engineers.
  • Solid programming skills in Python and SQL, and familiarity with tools such as Git, CI/CD workflows, Docker, and Kubernetes.
  • Experience with data pipeline orchestration tools (e.g., Dagster) and modern data stack components.

Why Join Us

  • Help shape the future of responsible, high‑impact data and AI solutions in infrastructure, engineering, and consulting.
  • Work alongside a mature team with a strong mandate to improve data engineering within our organisation.
  • Shape our enterprise data engineering practice from the ground up and be a foundational contributor to our overall enterprise data architecture and strategy.
  • Lead and mentor within a collaborative, fast‑growing team focused on innovation with purpose.
  • Gain exposure to diverse, meaningful projects that create long‑term social and environmental value.

Benefits

Health and wellbeing



  • Private medical insurance for all UK colleagues.
  • Health cash plan to support everyday health costs and treatments.
  • Access to Peppy, providing free support from menopause experts for all UK colleagues.
  • A variety of wellbeing support is available through our comprehensive wellbeing programme, including access for you and your family.
  • Ability to flex your salary to opt into a wide range of health benefits, many of which can be extended to your family too.

Financial wellbeing



  • We match employee pension contributions between 4.5% and 7%.
  • Life assurance equal up to 4x your basic salary, with an option to increase the level of cover to 6x your salary.
  • Our income protection scheme provides a financial benefit, as well as absence and return to work support due to long‑term illness or injury.
  • Flexible benefits, including increased life assurance cover, critical illness insurance, payroll saving and will writing.
  • As an independently owned business we share the financial success of the business with all our colleagues in various ways including annual bonus schemes.

Lifestyle



  • A minimum of 33‑35 days holiday each year, inclusive of public holidays and dependent on level, with the ability to buy or sell leave through our flexible benefits programme.
  • Holiday entitlement increased to a minimum of 35 days after 5 years’ service.
  • Variety of employee saving schemes and discounts from high‑street retailers.

Enhanced family and carers leave



  • Enhanced family leave policies, including 26 weeks paid maternity and adoption leave, and two weeks paid paternity/partner leave.
  • Our shared parental leave matches maternity leave meaning we pay up to 24 weeks at full pay.
  • Up to five additional days leave are provided for those with significant caring responsibilities, two of which are paid.

Learning and development



  • Primary annual professional institution subscription.
  • A broad range of opportunities to enhance both technical and soft skills through mentoring, formal training, and self‑development options.

Networks, communities, and social outcomes



  • Join a wide range of groups including our Advanced Employee Networks which support our LGBTQ+, gender, race and ethnicity, disability, and parents/carers communities.
  • Make a difference within our communities through our social outcomes.

Equality, Diversity, and Inclusion

We put equality, diversity, and inclusion at the heart of our business, seeking to promote fair employment procedures and practices to ensure equal opportunities for all. We encourage individual expression in our workplace and are committed to creating an inclusive environment where everyone feels they can contribute.


Accessibility

If you are disabled or need any support to enable you to apply or attend an interview, please contact us at and we will talk to you about how we can support you.


Seniority level

Mid‑Senior level


Employment type

Full‑time


Job function

Information Technology


Industries

Civil Engineering


Job Ref: 11222


Contract Type: Permanent


Work Pattern: Full Time


Market: Various


Discipline: Digital design


Recruiter Contact: Nikki George


Apply now, or for more information about our application process, click here.


#J-18808-Ljbffr

Related Jobs

View all jobs

Principal Data Engineer/Architect

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer

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.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.