AWS DATA ENGINEER (HYBRID / REMOTE BRAZIL)

Description

Summary: Seeking a Senior AWS Data Engineer to design, develop, and optimize cloud-based data platforms supporting enterprise analytics and business intelligence. Highlights: 1. Build scalable cloud data solutions on AWS using Glue, Spark, and Redshift. 2. Collaborate with Data Engineers and Scientists in an international environment. 3. Work on enterprise-scale AWS cloud projects and modern data engineering. #### **AWS DATA ENGINEER (HYBRID / REMOTE BRAZIL)** Portuguese company hires for hybrid position Location: Brazil (any location) * ️ Only candidates already based in Brazil will be considered Work Model: **Hybrid for candidates living in state capitals** and **Remote for candidates living in countryside/cities outside the state capitals** ️ Language Requirements: English C2 (Advanced/Fluent) – **Mandatory** (there will be direct contact with an international client) Seniority: Senior (6\+ years) Compensation: Please inform your salary expectations when applying. * ️ Instructions: Please send your CV in English and make sure to include all skills and experience that match the requirements of the opportunity. This will significantly increase your chances of success. #### **Build Scalable Cloud Data Solutions on AWS** We are looking for an experienced AWS Data Engineer to design, develop, and optimize modern cloud\-based data platforms supporting enterprise analytics and business intelligence initiatives. You will work with large\-scale datasets, build high\-performance ETL pipelines, optimize distributed data processing, and collaborate with Data Engineers, Data Scientists, and business stakeholders in an international environment. If you are passionate about cloud\-native data engineering and scalable architectures, this opportunity is for you. #### **The Professional We Are Looking For** We are seeking a highly technical Data Engineer with deep expertise in AWS data services, distributed processing, and modern data warehouse architectures. The ideal candidate combines strong programming skills with practical experience building reliable, scalable, and high\-performance data pipelines while following cloud engineering best practices. You should be comfortable working in enterprise environments, solving complex data challenges, and collaborating with global teams. #### **Key Responsibilities** You will be responsible for: * Design, develop, and implement enterprise data solutions using **AWS Glue, Apache Spark, and Amazon Redshift**. * Collaborate with Data Engineers and Data Scientists to understand business requirements and translate them into scalable data pipelines. * Build and manage ETL processes using **AWS Glue**. * Develop and optimize distributed data processing workflows using **Apache Spark**. * Design and maintain data models and schemas in **Amazon Redshift**. * Monitor, troubleshoot, and optimize data pipelines to ensure data quality, reliability, and performance. * Document data architectures, engineering processes, and best practices. * Support enterprise reporting and analytics initiatives through reliable cloud data platforms. #### **Mandatory Requirements (Eliminatory)** * ️ **All requirements below are mandatory and eliminatory.** Candidates who cannot clearly demonstrate these qualifications in their CV are unlikely to proceed in the recruitment process. **Education** ✔ Bachelor's Degree in: * Information Systems * Computer Science * Data Engineering * or a related field #### **Mandatory Experience** * English **C2 (Advanced/Fluent)** with the ability to communicate confidently in an international environment. * Proven experience developing cloud data solutions on **AWS**. * Strong hands\-on experience with: * AWS Glue * Apache Spark * Amazon Redshift * Strong programming skills using **Python** or **Scala**. * Solid understanding of **Data Warehousing** concepts and best practices. * Strong SQL skills. * Experience with relational database management systems. * Experience designing and implementing ETL pipelines. * Experience developing scalable enterprise data processing solutions. * Strong analytical and problem\-solving skills. #### **Nice\-to\-Have Skills** The following qualifications will be considered a strong advantage: * Experience with enterprise\-scale cloud data platforms. * Data Lake and Lakehouse architectures. * Infrastructure as Code (IaC). * CI/CD pipelines for data engineering. * Data governance and data quality initiatives. * Experience working with international teams. * Financial Services industry experience. #### **What You'll Find in This Opportunity** * Enterprise\-scale AWS cloud projects. * Modern Data Engineering environment. * Collaboration with Data Engineers and Data Scientists. * Exposure to large\-scale distributed data processing. * Opportunity to design scalable cloud\-native data architectures. * International, collaborative, and innovation\-driven environment. #### **Before Applying, Ask Yourself These 5 Questions** ✅ Do I have proven hands\-on experience with **AWS Glue, Apache Spark, and Amazon Redshift** in production environments? ✅ Does my CV clearly demonstrate experience building **ETL pipelines**, designing cloud data solutions, and working with enterprise\-scale datasets? ✅ Am I proficient in **Python or Scala**, as well as advanced SQL for data engineering projects? ✅ Do I have a strong understanding of **Data Warehousing** concepts and cloud\-based data architectures? ✅ Am I fluent in English (**C2**) and comfortable collaborating with international teams and stakeholders? If you answered **"No"** to one or more of these questions, we recommend carefully reviewing your fit before applying. * **️ Important** This position is intended for an **AWS Data Engineer** with strong experience designing and implementing enterprise data platforms. Candidates whose experience is primarily focused on Business Intelligence, Reporting, Data Analysis, or Software Development, without significant hands\-on expertise in AWS data engineering technologies, are unlikely to meet the expectations for this role. #### **Keywords That Should Appear in Your CV** **AWS Data Engineer, Data Engineer, Amazon Web Services, AWS, AWS Glue, Apache Spark, Spark, Amazon Redshift, Redshift, ETL, Data Pipelines, Data Engineering, Data Processing, Python, Scala, SQL, Data Warehousing, Data Warehouse, Data Modeling, Cloud Data Platform, Cloud Architecture, Big Data, Distributed Computing, Data Integration, Data Transformation, Data Quality, Enterprise Data, Relational Databases, Analytics, Business Intelligence, AWS Cloud, Data Lake, Lakehouse, Performance Optimization, Enterprise Data Solutions** \#EP