Job Title: Data Engineer, EDM III BRL- 10 Years
Location : Brazil remote
Project Duration: 6 months
Job description:
Primary Skills
SQL, Python, Pyspark, Airflow, AWS, MLOPs
Secondary Skills
Communication, leadership, project management
Position Overview
The BMP (Business Model and Pricing) Analytics team is seeking an experienced Data Engineer to support business performance management and strategic decision-making through scalable data infrastructure and engineering solutions. The team partners closely with leadership, finance, operations, and business stakeholders to enable reliable, high-quality data access, support advanced analytics, and drive data-informed actions across the organization.
The Data Engineer will play a critical role in designing, building, and maintaining robust data pipelines, data models, and foundational data assets that power analytics, reporting, and emerging AI/ML capabilities. This role requires strong engineering rigor, a deep understanding of data systems, and the ability to collaborate across technical and business teams.
The ideal candidate has a proven track record of building scalable data solutions in a fast-paced, cross-functional environment and is comfortable balancing foundational data platform work with evolving analytics and AI-driven initiatives.
What you will do
You have a strong engineering and problem-solving mindset. You translate business and analytical needs into scalable, reliable data solutions and architectures.
You design, build, and maintain scalable data pipelines and data models that support business performance monitoring, analytics, and reporting, while contributing to the development of the BMP Data Foundation across Hive, Snowflake and data lake environments.
You support the buildout of data products and applications, including contributing to Streamlit-based pipelines and the development of chatbot capabilities to enhance data access and user interaction.
You collaborate closely with analytics, data science, and business teams to ensure data availability, quality, and usability for dashboards, reporting, and advanced analyses.
You enable and support the buildout of advanced analytics, machine learning and AI capabilities, ensuring the necessary data infrastructure, pipelines, and environments are in place to support model development and deployment.
You contribute to the design and evolution of the data and ML ecosystem, helping establish the infrastructure, processes, and foundations required to scale AI/ML initiatives across the organization.
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Minimum Qualifications
• Master's degree in computer science, Data Engineering, Engineering, or a related quantitative field.
• 5+ years of experience in data engineering, data platform development, or related roles.
• Strong experience with SQL and at least one programming language (Python or equivalent).
• Familiarity with big data and distributed processing frameworks (e.g., Spark / PySpark).
• Experience building and maintaining data pipelines and working with modern data architectures.
• Experience with orchestration tools (e.g., Airflow) and pipeline automation.
• Experience with cloud-based data platforms (e.g., AWS) and data warehousing solutions (e.g., Snowflake).
• Strong understanding of data modeling, data quality, and data governance principles.
• Experience with version control systems (Git) and collaborative development workflows.
• Strong problem-solving skills and ability to work with ambiguous requirements.
• Excellent communication skills and ability to collaborate with both technical and non-technical stakeholders.
• Fluent in English.
Preferred Qualifications
• Experience working with data lake architectures and hybrid data environments.
• Experience supporting machine learning pipelines and infrastructure.
• Exposure to data applications (e.g., Streamlit) and conversational interfaces (chatbots).
• Experience with AI-assisted development tools and practices.
• Experience contributing to documentation and knowledge-sharing platforms (e.g., Confluence).
• Experience working in a matrixed, global organization.