Senior Full Stack Engineer
Listed on 2026-01-19
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IT/Tech
Data Engineer
Mott Mac Donald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices. We work across incredible global industries, delivering exciting work that is defining our future and making an important societal impact in the communities we serve. Our people power our performance – we succeed when they do. With countless opportunities to collaborate, learn, and grow, the possibilities for excellence are as varied as every individual.
Whether you want to grow as a subject matter expert or broaden your experience with roles across our international community, you’re surrounded by global specialists who want to combine their expertise and champion you to be your best. As a proudly employee‑owned business, we benefit our clients, our communities, and each other, investing in creating the right space for everyone to feel empowered, included, and valued.
Whatever your ambition, Mott Mac Donald is where people come to be brilliant.
Location/s:
London | Recruiter contact:
Nikki George
We’re looking for a Senior Data Engineer to help shape and develop our enterprise data architecture. This position is ideal for someone who combines deep technical expertise with strong stakeholder engagement skills. You’ll be delivering the data foundations that enable impactful AI and analytics solutions across our global engineering, consulting, and infrastructure business.
In this role 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:
Support other group‑wide architects to define and implement data architecture patterns across systems and domains to support analytical, AI, and operational use cases.
- Extensive 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).
- Excellent communication and stakeholder engagement skills—able to bridge technical detail and strategic business value.
- 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.
- Help shape the future of responsible, high‑impact data and AI solutions in infrastructure, engineering, and…
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