Senior Engineer

Vaga não está no LinkedIn

🕒 2 dias atrás

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

🧑‍💻 Engenheiro Full-stack

👻 Score fantasma 15%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Logo of Nexus Cognitive

Nexus Cognitive

51 - 200 funcionários

Fundada em 2018

💼 Consultoria

📣 Marketing

📦 Logística

💰 Series unknown em 2024-07

Consulting • Marketing • Logistics

A Nexus Cognitive é uma camada de inteligência composível e plataforma de dados abertos que se posiciona acima dos sistemas de dados empresariais para tornar os dados prontos para IA sem substituir a infraestrutura existente. Ela oferece um portal de consulta universal, enriquecimento automático, governança centralizada e um serviço de pilha completa gerenciado que possibilita implantações de IA rápidas (em 30 dias), menor custo total de propriedade (TCO) e segurança e conformidade em nível empresarial. A Nexus Cognitive potencializa a inteligência de receita, cliente, operacional e de risco ao unificar dados de armazéns, data lakes e plataformas na nuvem, preservando o contexto de negócios e minimizando a proliferação de ferramentas.

Descrição

• Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and deliver data from internal and external sources • Develop and optimize data models and schemas supporting analytics, reporting, and downstream application needs • Monitor pipeline health, troubleshoot data quality issues, and implement alerting and observability practices • Partner with analytics, product, and engineering teams to translate data needs into durable data solutions • Improve performance, scalability, and cost-efficiency of existing data infrastructure • Write technical documentation and contribute to standards for testing, code review, and deployment • Participate in on-call or incident response rotations as needed to support production data systems

🎯 Requisitos

• 4+ years of professional experience in data engineering or a closely related discipline • Strong proficiency in SQL and at least one programming language commonly used for data engineering (e.g., Python, Scala, or Java) • Hands-on experience building and operating ETL/ELT pipelines in a production environment • Experience working with cloud data platforms (e.g., AWS, GCP, or Azure) and modern data warehousing tools • Solid understanding of data modeling, data quality, and pipeline orchestration concepts • Comfort working with large, complex datasets and diagnosing data issues independently • Experience with orchestration tools such as Airflow, Dagster, or similar • Familiarity with streaming data technologies (e.g., Kafka, Kinesis) • Experience with dbt or similar transformation frameworks • Exposure to infrastructure-as-code practices (e.g., Terraform) • Prior experience supporting analytics or data science teams directly

🏖️ Benefícios

• A collaborative team culture built on curiosity and respect • Challenging work where your contributions clearly matter • A leadership team that invests in learning and development • Opportunity to work at the intersection of cloud, data, and AI innovation

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