Fundment is a fast-growing wealth infrastructure company combining proprietary technology with exceptional customer service to transform the £3 trillion UK wealth management market for financial advisers and their clients. We’re growing our Data, Analytics & AI function—and looking for a hands-on Data Engineer to help unlock the potential of our data.
Reporting to our Head of Data & Analytics, you’ll design, build and operate the pipelines, models and infrastructure that power our data platform. Your work will enable AI products, better decisions across Leadership, Sales, Engineering and Finance, and better service for advisers.
Working with Product, Operations, Sales and Engineering, you’ll help ensure our data is accurate, scalable, secure and fit for purpose as we grow.
Build batch and real-time streaming pipelines using internal and external data sources.
Optimise querying and transformation of structured and unstructured data.
Create a unified data and metrics framework with consistent KPI definitions.
Implement data observability and quality monitoring, with centrally tracked and governed data assets to protect clients.
Provision and control data components through Infrastructure as Code, keeping code changes tracked and auditable.
Monitor and optimise the cost efficiency of our GCP data platform.
Help technical and non-technical colleagues use data, analytics and AI effectively and securely.
Turn requirements into technical specifications and project plans, delivering from concept to production.
Identify opportunities for more accurate and timely data-driven decisions.
Experience: Proven experience (4+ years) in data engineering.
Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Technical skills:
Advanced proficiency in SQL and Python for data manipulation and analysis
Experience in data processing and developing and deploying infrastructure on a public cloud platform such as GCP, AWS or Azure.
Experience building and maintaining data transformation layers using dbt.
Experience with data observability and monitoring
Experience with containerization technologies including CloudRun and Docker.
Experienced with Infrastructure as Code (e.g. Terraform)
Communication: Excellent written and verbal communication, presentation and interpersonal skills
Experience in a startup or high-growth environment.
Knowledge of data privacy and AI regulation, preferably within financial services.
Familiarity with real-time data processing and streaming analytics.
Experience in GCP data processing suite, like BigQuery, Dataflow and Datastream
GCP Professional Data Engineer or Professional Machine Learning Engineer certifications.
Collaborative: listening, communicating and working towards shared goals.
Innovative: pushing boundaries and improving our solutions.
Supportive: helping each other grow and succeed.
Flexible: adapting to team and client needs while supporting work-life balance and effective outcomes.
Trustworthy: acting consistently and transparently and delivering on our promises.
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