Lead GCP Data Engineer, Homeprotect

• 5+ years’ experience as a Data Engineer, including building and operating production-grade data pipelines and data products
• 3+ years building on GCP in a production environment
• Strong ability to design and implement reliable data pipelines and make good engineering trade-offs
• Strong hands-on experience with: BigQuery, Cloud Storage (GCS), Terraform, dbt, Kafka (and streaming data concepts), Dataflow, Cloud Run (jobs and or services), Cloud Composer (Airflow) or equivalent orchestration tooling
• Experience designing and operating pipelines across multiple ingestion patterns, including CDC, APIs, SFTP, streaming etc
• Strong understanding of medallion architecture (Bronze, Silver, Gold) and how to implement it in a modern analytics platform
• Trong experience working within Agile methodologies (Scrum) and contributing positively to team rituals and delivery cadence
• Strong communication: you can explain technical decisions clearly to engineers and non-engineers, and you document just enough to scale the team

Desirable

• This role leads the design and operation of a modern, integrated data governance strategy that ensures our data is trusted, compliant, and well documented across Homeprotect
• As part of the Data team, you will set and implement the standards, policies, and frameworks that underpin our analytics, ML, and AI roadmap, while fostering a culture of data‑driven decision‑making
• You will work closely with Data Engineering and business stakeholders to define clear data ownership and stewardship, enable responsible access to data, and elevate data literacy across the organisation
• The role combines strategic leadership with hands‑on delivery
• This is a unique opportunity to join HomeProtect at the start of building a brand new GCP Data Analytics Platform
• We are looking for an enthusiastic, experienced lead engineer who can help drive, architect, and deliver a best-in-class platform from the ground up
• You will report directly to the Head of Data Engineering and provide technical leadership across the data engineering team, helping to shape design decisions, set engineering standards, and ensure delivery remains aligned to our platform direction
• Shape implementation choices and guide the team through trade-offs (cost, reliability, security, operability, maintainability)
• Set and maintain engineering standards (patterns, templates, coding practices, testing expectations, documentation)
• Create technical clarity through lightweight design notes and ADRs that help the team move faster with fewer surprises
• Lead end-to-end delivery of data products on GCP, from onboarding new sources through to curated datasets, marts, and business-facing outputs
• Own ingestion design and implementation at a platform level: selecting and refining patterns, establishing reusable templates, and ensuring ingestion is reliable, scalable, and easy to operate
• Build and improve transformation and modelling workflows in the warehouse, with a strong focus on correctness, performance, and cost control
• Work in an Agile way: contribute to planning, estimation, delivery cadence, and continuous improvement
• Maintain a strong focus on delivering measurable value to stakeholders, prioritising work that improves decision making and accelerates insights aligned with business needs
• Design pipelines and jobs to be production-grade: idempotent, observable, resilient to failure, and easy to support
• Champion automated testing and release practices so changes can be safely promoted through environments with minimal manual effort
• Mentor and upskill data engineers through pairing, structured reviews, knowledge sharing, and best practise guidance
• Be a go-to technical reference for the team, providing calm, high-quality support when work is ambiguous or high pressure
• What success looks like (first 90 days):
• You are successfully ingesting new data sources using a combination of existing and newly developed ingestion patterns (CDC, APIs, SFTP, streaming), and improving those patterns as you go
• You are building out new dbt warehouse models with strong engineering discipline, helping establish repeatable standards for the team
• You are working directly with the business to understand new dimensional models and marts required, translating needs into clear modelling approaches and deliverable data products