Data Engineer

• Lead the design and delivery of scalable, resilient data pipelines into Big Query, integrating data from a wide range of internal systems, APIs, databases, files, webhooks and event streams.
• Shape the engineering approach across Google Cloud Platform (GCP), working with technologies including Big Query, Cloud Storage, Pub/Sub, Datastream and Cloud Composer/Airflow, alongside Terraform and infrastructure-as-code.
• Set and champion high engineering standards across data modelling, dbt (data build tool) transformations, testing, monitoring, documentation, deployment, version control and cost optimisation.
• Partner with teams across the firm to turn business needs into scalable, reusable data products, bringing together data from external and internal sources such as Companies House, HMRC, Exchange Online, Active Directory, iManage and Dayshape.
• Embed security, governance and data quality by design, ensuring appropriate controls around data lineage, access, GDPR compliance, least-privilege security and the handling of sensitive client, HR, payroll and financial information.
• Provide technical leadership to the wider team, reviewing designs and code, mentoring data engineers and analysts, and helping to strengthen engineering capability across the Innovation Team.
• Enable data to deliver real business value by working with developers and analysts to make warehouse outputs accessible through Power BI, automation workflows, AI agents and internal applications.
• Evaluate technology and integration options, making pragmatic build-versus-buy recommendations that balance business value, security, scalability, supportability and cost.
• Champion data enablement across Menzies, supporting colleagues to confidently access, understand and use data safely and effectively.
• Help shape the Innovation Team roadmap, prioritising strategic, repeatable platforms and solutions that can deliver value across the firm rather than one-off fixes.

  We're looking for an experienced and curious data professional who combines strong technical expertise with a practical, people-focused approach. You'll be comfortable taking ownership, making sound technical decisions and bringing others with you; whether you're mentoring colleagues, partnering with stakeholders or turning a complex business challenge into a scalable solution.

You don't need to tick every box. We're interested in people who can bring the right mix of experience, technical capability and ambition to help us continue developing our data and innovation capability. What you'll bring

• Strong hands-on experience in data engineering, analytics engineering or data platform roles, typically gained over 5+ years, with experience operating at a senior or leadership level.
• Advanced SQL and Python skills and experience using them to build reliable, production-ready data solutions.
• Strong experience with cloud data warehouses, ideally Big Query, and a good working knowledge of the wider Google Cloud Platform (GCP) ecosystem.
• Experience with modern data engineering tools and practices such as Airflow/Cloud Composer, dbt, Git/Git Hub, CI/CD and Terraform or other infrastructure-as-code tooling.
• A solid understanding of data modelling, dimensional modelling, orchestration, testing, data quality and operational monitoring, with a focus on building solutions that are scalable and maintainable.
• Experience designing and operating production-grade data pipelines, integrating data from sources such as APIs, databases, flat files, webhooks and message queues.
• A strong appreciation of data security and governance, including GDPR, role-based access, secrets management and the responsible handling of sensitive information.
• The ability to take an ambiguous business challenge and turn it into a clear, pragmatic technical solution, balancing immediate needs with longer-term value.
• Strong communication and stakeholder skills, with the confidence to make complex technical concepts accessible to non-technical audiences and influence decisions at different levels.
• Collaborative leadership style, with a genuine interest in coaching others, sharing knowledge and raising engineering standards across the team., A degree or equivalent experience in computer science, data engineering, software engineering, mathematics, statistics or a related technical discipline would be beneficial. Google Cloud, dbt or other relevant data engineering certifications are also welcomed, although practical experience and demonstrable expertise are just…