Data Engineer

Fundment is a fast-growing wealth infrastructure company, building on our cutting-edge digital investment system to transform the £3 trillion UK wealth management market. We are passionate about revolutionising the investment experience for financial advisers and their clients by combining our innovative proprietary technology with exceptional customer service. As we scale, we are growing our multi-disciplinary Data, Analytics & AI function to unlock the full potential of our data assets.

About the Role

With our highly scalable technology platform, high-quality data sits at the heart of everything we do. This is a high-impact, hands-on engineering role with the opportunity to help build and scale Fundment's data platform.

Reporting to our Head of Data& Analytics, you will design, build and operate the data pipelines, models and infrastructure that power our data platform. This enables us to develop industry-leading AI products, make better business decisions across Leadership, Sales, Engineering and Finance, and ultimately serve advisers in the wealth management industry better.

Working closely with stakeholders across Product, Operations, Sales and Engineering, you will ensure that our data is accurate, scalable, secure and fit for purpose as Fundment continues to grow.

Key Responsibilities:

Data Ingestion and Processing:

• Design and deliver complex data pipelines for both batch and real-time streaming data processing from both internal and external data sources.
• Build and optimise our query and transform capabilities across both structured and unstructured data.
• Define and implement a unified data and metrics framework to ensure consistent definitions and understanding of KPIs across the organisation.

Quality and compliance:

• Implement data observability and data quality monitoring to ensure our data is continually able to support our operations and drive business growth.
• Make data assets centrally tracked and governed, to allow us to operate data and analytics in a way that avoids harm to clients.
• Ensure that all data components are provisioned and controlled through Infrastructure As Code (IaC) and that code changes are tracked and auditable.
• Monitor, analyse, and optimise the cost efficiency of our GCP data platform.

Stakeholder Management:

• Collaborate with cross-functional teams across the company to help both technical and non-technical users leverage our data, analytics and AI capabilities in an optimal and secure way.
• Translate requirements into technical specifications and project plans, overseeing execution from conception to production.
• Identify new ways to use data better, either more accurately or more timely, in our decision-making

Person Specification:

• 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 , developing and deploying infrastructure on a public cloud platform like GCP, AWS or Azure
• Experience building and maintaining data transformation layers using dbt.
• Experience with data observability and monitoring
• Experience with containerization technologies including Cloud Run and Docker.
• Experienced with Infrastructure as Code (e.g. Terraform)
• Communication:
  Excellent written and verbal communication, presentation and interpersonal skills

Preferred Skills/

Experience:

• 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 Big Query, Dataflow and Datastream
• GCP Professional Data Engineer or Professional Machine Learning Engineer certifications.

Our…