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Senior Full Stack Engineer – Data Platform
Vaga remota de Senior Full Stack Engineer (Analytics Platform) com fit claro de localização do candidato.
Publicada18 de jun. de 2026
Países elegíveis6 países aceitos
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
BelizeColômbiaRepública DominicanaHondurasNicaráguaPeru
Resumo da vaga
Senior Full Stack Engineer – Data Platform
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
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
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Fluxo de contratação
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