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Senior Full Stack Engineer – Data Platform
Rol remoto de Senior Full Stack Engineer (Analytics Platform) con fit claro de ubicación del candidato.
Publicado18 jun 2026
Países elegibles6 países aceptados
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
BeliceColombiaRepública DominicanaHondurasNicaraguaPeru
Resumen del rol
Senior Full Stack Engineer – Data Platform
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
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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