[Job - 29349] Senior Data Developer (AWS), Brazil

🕒 Maio 15

🇧🇷 Brasil – Remoto

⏰ Tempo Integral

🟠 Sênior

☁️ Engenheiro de Cloud

👻 Score fantasma 45%

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.

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CI&T

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

Fundada em 1995

💼 Consultoria

🏥 Saúde

📣 Marketing

💰 $5.500.000 Venture Round em 2014-04

Consulting • Healthcare • Marketing

CI&T é especialista global em transformação tecnológica, ajudando organizações a trilhar sua jornada tecnológica. Com serviços que vão de modernização de aplicações e soluções em cloud a data analytics com IA e experiência do cliente, a CI&T capacita negócios a acelerar o crescimento e maximizar a eficiência operacional. A empresa enfatiza design de produtos digitais, consultoria estratégica e experiências imersivas, assegurando um suporte robusto para empresas de diversos setores.

Descrição

•Design and build end-to-end data pipelines across the RAW, Silver, and Gold layers of the Medallion Architecture, ensuring reliability, performance, and maintainability at each stage •Architect data ingestion, transformation, standardization, and serving processes, structuring data flows from diverse and heterogeneous sources into a coherent analytical foundation •Model data for analytical consumption following Data Warehouse best practices, including Star Schema design and dimensional modeling suited for business intelligence and AI-readiness •Identify, evaluate, and consolidate new data sources relevant to agronomic business objectives, proactively engaging stakeholders to understand, obtain, and validate data availability and quality •Interact with business stakeholders and client leadership to translate domain requirements into data architecture decisions, challenging assumptions and proposing solutions grounded in technical evidence •Manipulate, optimize, and serve data in multiple formats — including Parquet, CSV, and geospatial datasets — tailored to the consumption needs of downstream AI applications and map-based visualizations •Manage and configure cloud infrastructure end-to-end, including storage, compute, access control, serverless functions, data cataloging, and event-driven processing on AWS •Own deployment and CI/CD practices for data pipelines — including repository management, branching strategy, test gates, and automated deploy workflows via GitLab •Support the creation of the data layer that will feed AI/ML applications, ensuring data quality, structure, and availability meet the requirements of machine learning workflows — without directly developing the models themselves •Operate as a proactive technical partner in a greenfield environment: question, propose, experiment, and iterate with the team rather than execute in isolation

🎯 Requisitos

•English proficiency at B2 level or above — ability to explain technical flows, engage in discussions, ask clarifying questions, and collaborate effectively with international stakeholders (accent is not a barrier; communication clarity is) •Solid hands-on experience with AWS, covering the full infrastructure spectrum: S3, IAM (permissions and security configuration), Redshift, Lambda (serverless use cases), and Glue (including Glue Catalog for metadata management); ability to evaluate trade-offs between services for different pipeline scenarios •Experience with Terraform or equivalent Infrastructure-as-Code (IaC) tooling, applied recurrently in real data engineering projects — not just theoretical knowledge •Proficiency with GitLab for source control, CI/CD pipeline configuration, deployment workflows, and test gate management — specifically GitLab, not just generic Git experience •Strong proficiency in SQL, including complex query writing, analytical transformations, and performance tuning for data warehouse environments •Strong proficiency in PySpark, applied to large-scale distributed data processing — including partitioning strategies (e.g., by day/month/year), volume handling (tens to hundreds of GB), and performance optimization •Experience with Databricks, used in the context of data engineering pipelines and lakehouse architectures, including migration and deployment scenarios •Analytical data modeling expertise, with solid knowledge of Star Schema and dimensional modeling applied to data warehousing and business intelligence environments •Hands-on experience with the Medallion Architecture (RAW / Silver / Gold layers), including manipulation and optimization of Parquet and CSV files •Experience integrating and consolidating data from multiple heterogeneous sources, ensuring consistency, traceability, and analytical readiness •Mindset suited for greenfield projects: proactive, solution-oriented, comfortable with ambiguity, and able to contribute to architectural decisions — not just execute predefined tasks

🏖️ Benefícios

•Health and dental insurance •Meal and food allowance •Childcare assistance •Extended paternity leave •Partnership with gyms and health and wellness professionals via Wellhub (Gympass) TotalPass; •Profit Sharing and Results Participation (PLR); •Life insurance •Continuous learning platform (CI&T University); •Discount club •Free online platform dedicated to physical, mental, and overall well-being •Pregnancy and responsible parenting course •Partnerships with online learning platforms •Language learning platform