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Job Title Senior Full Stack Engineer – Data Platform
Location Remote
Time Zone Flexible / Aligned to HQ Time Zone
Role Overview We are building the data backbone for the next generation of AI-powered automation — and we need a Senior Full Stack Engineer who can operate across the full stack: from data ingestion pipelines to the polished frontend dashboards our enterprise customers rely on.
This role is ideal for an engineer who thrives where data engineering meets product engineering. You will own the interfaces and services that make complex data meaningful and actionable — and you will work alongside automation engineers to ensure that RPA agents have the structured, reliable data they need to function intelligently.
Key Responsibilities
Build and maintain frontend experiences for our data platform, including dashboards, data explorers, and workflow builders
Design and implement RPA agent integrations that interact with structured and unstructured data sources
Develop APIs and services that expose platform data to both internal consumers and customer-facing products
Contribute to the semantic layer that contextualises data for AI agents — including tagging, categorisation, and metadata enrichment
Collaborate with data engineers to ensure frontend and API layers align with underlying data models
Drive performance and scalability improvements across frontend and backend components
Required Qualifications
Senior-level full stack experience with strong frontend depth in React and TypeScript
Experience building data platform or BI-adjacent frontends including dashboards, query interfaces, and real-time data views
Familiarity with RPA tooling and automation workflow design
Understanding of data modelling, ETL patterns, and API-first architecture
Experience with cloud data services such as Snowflake, BigQuery, or Redshift
Strong attention to UX detail and the ability to translate complex data into clear, usable interfaces
Must have prior remote work experience and proven ability to work independently within a distributed team
Preferred Qualifications
Experience with semantic metadata layers or data cataloguing tools
Background in enterprise SaaS product development
Knowledge of streaming data technologies such as Kafka or Kinesis
Exposure to dbt, Airflow, or similar data pipeline tooling
Tools & Technology
React / TypeScript
Python / Node.js
Cloud data warehouses (Snowflake, BigQuery, or similar)
RPA platforms (UiPath, Power Automate, or similar)
REST and event-driven APIs
Slack, Zoom, Google Workspace
Please Note It is crucial that you complete the application form in full. As part of the application process, you will be required to complete a short technical assessment. If your application is successful, you will receive an email confirming next steps. Applications that are not completed in full will not be considered for any open roles.
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