Data Engineer

Vaga não está no LinkedIn

🕒 Ontem

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

👻 Score fantasma 24%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

Candidatar-se

Encontrar Vagas Remotas Similares

Configurar Alerta de Email para Novas Vagas

📊 Verifique sua pontuação de currículo para esta vaga

Melhore suas chances de conseguir uma entrevista verificando sua pontuação de currículo antes de se candidatar.

Enviar Currículo

Rayda

SiteLinkedInTodas as Vagas

11 - 50 funcionários

📦 Logística

💼 Consultoria

🏥 Saúde

💰 Pre seed em 2023-02

Logistics • Consulting • Healthcare

Rayda é uma plataforma SaaS que automatiza a gestão do ciclo de vida de dispositivos de funcionários para empresas em âmbito global. Ela lida com aquisição, pré-configuração, envio internacional, rastreamento, manutenção, limpeza segura de dados, recolhimento, armazenamento, seguro e descarte sustentável em mais de 170 países, permitindo que as equipes de TI, RH e operações equipem rapidamente e de forma confiável os funcionários remotos. A Rayda centraliza o rastreamento e documentação de dispositivos, reduz os tickets e custos relacionados a dispositivos e acelera os fluxos de trabalho de integração e desligamento para clientes empresariais distribuídos.

Descrição

• Design, build, deploy and maintain scalable, production-grade data pipelines and ETL/ELT workflows. • Integrate data from operational databases, APIs, CRM systems, product analytics, IT ticketing platforms and device telemetry. • Evaluate and implement appropriate data warehouses, lakehouses and analytical databases. • Develop reliable data models and reusable datasets for business reporting, product analytics and customer-facing applications. • Build data infrastructure supporting customer intelligence dashboards, anomaly detection, predictive insights and AI-powered recommendations. • Establish data quality standards, automated validation, monitoring, alerting and recovery mechanisms. • Improve data collection, instrumentation, schema management and data documentation. • Implement secure data processing practices, access controls and customer-level data isolation. • Optimise data storage, processing performance, scalability and infrastructure costs. • Collaborate with Product, Engineering, Finance and Operations to translate business requirements into reliable data solutions. • Maintain technical documentation covering data architecture, integrations, pipeline dependencies and operational procedures.

🎯 Requisitos

• Demonstrated experience designing, deploying and maintaining production-grade data pipelines. • Strong SQL proficiency and experience working with relational databases and complex datasets. • Hands-on experience with ETL/ELT processes, incremental data processing, transformations and pipeline monitoring. • Proficiency in Python or another suitable data engineering programming language. • Experience integrating databases, REST APIs, SaaS platforms and external data sources. • Experience designing and implementing data warehouses, lakehouses or analytical data platforms. • Strong knowledge of data modelling, data quality, validation and schema management. • Familiarity with cloud infrastructure, data storage, access controls and production reliability. • Ability to evaluate technical architecture based on performance, scalability, cost and business requirements. • Strong analytical, problem-solving and independent execution skills. • Experience working with B2B SaaS platforms and multi-tenant architectures. • Familiarity with dbt, Airflow, Dagster, ClickHouse, BigQuery or Snowflake. • Experience with device telemetry, time-series data, IT operations or cybersecurity platforms. • Knowledge of event-driven architecture, streaming data and high-volume operational events. • Experience building data infrastructure for AI, machine learning or predictive analytics. • Previous experience in an early-stage or high-growth technology environment.

🏖️ Benefícios

• Opportunity to build foundational data infrastructure supporting a growing global IT operations platform. • Ownership of important engineering architecture and technical decisions. • Opportunity to develop data solutions that directly influence customer-facing product capabilities. • Exposure to data engineering, AI-powered intelligence and emerging IT operations technologies. • Cross-functional collaboration with Product, Engineering, Finance and Operations. • Opportunity to solve complex, real-world data challenges and contribute to Rayda's product evolution.