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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Data Engineer based in Brazil.
This role is a senior technical leadership opportunity focused on designing and scaling modern, cloud-native data platforms that power analytics, machine learning, and business intelligence across multiple industries. You will play a key role in shaping end-to-end data architecture, ensuring that data is reliable, secure, and optimized for performance at enterprise scale. The position combines hands-on engineering with strategic leadership, working closely with data scientists, analysts, and product teams. You will influence technical direction, define engineering standards, and mentor teams of data engineers across different levels of seniority. A strong focus is placed on building robust ETL/ELT pipelines, improving data quality, and enabling self-serve analytics capabilities. This is a highly impactful role in a fast-paced, cloud-driven environment where engineering excellence and architectural vision directly drive business value.
Accountabilities:
- Lead the design, development, and maintenance of scalable, cloud-based data platforms and enterprise data architectures supporting analytics and machine learning use cases.
- Architect and optimize ETL/ELT pipelines for batch and near real-time data processing, ensuring high performance, reliability, and cost efficiency.
- Define and enforce data engineering best practices, governance standards, coding guidelines, and architectural principles across teams.
- Design and implement data modeling approaches such as Star Schema, Snowflake Schema, and Data Vault to support analytical and operational needs.
- Build and manage orchestration frameworks using tools such as Airflow, dbt, or equivalent technologies.
- Establish robust frameworks for data quality, monitoring, observability, lineage, and system reliability.
- Collaborate with Data Science, Analytics, and Product teams to deliver production-ready datasets and support advanced analytics initiatives.
- Lead technical discussions, architecture decisions, and code reviews while mentoring and guiding Data Engineers across multiple levels.
- Ensure data security, privacy, and compliance standards are embedded across all data solutions.
- Contribute to strategic initiatives involving analytics platforms, machine learning workflows, and enterprise data modernization.
Requirements:
- 8+ years of experience in Data Engineering, Data Architecture, or Data Platform roles, including senior or principal-level responsibilities.
- Strong expertise in designing and implementing large-scale, cloud-native data solutions.
- Advanced SQL skills and strong proficiency in Python for data engineering and processing workflows.
- Extensive experience building and optimizing ETL/ELT pipelines in distributed environments.
- Hands-on experience with orchestration tools such as Airflow, dbt, or similar frameworks.
- Deep knowledge of data modeling, data warehouse design, and modern data lake architectures.
- Proven experience working with cloud platforms such as AWS, Azure, or GCP.
- Strong understanding of CI/CD practices applied to data platforms and pipelines.
- Experience with data governance, security, privacy, and data lineage best practices.
- Ability to lead technical initiatives, influence architectural decisions, and mentor engineering teams.
- Strong communication and stakeholder management skills, with an ability to collaborate across technical and business teams.
- Advanced English proficiency, with experience working in international and distributed environments.
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field (Master’s is a plus).
Benefits:
- Remote-first work model with flexibility
- Opportunity to work with global brands and innovative startups
- Exposure to large-scale, cloud-native data environments
- Access to learning platforms, courses, and certifications
- International and multicultural work environment
- Career growth opportunities across multiple business units and projects
- Participation in technical meetups, events, and knowledge-sharing sessions
- English classes and professional development support
- Birthday day off and additional well-being initiatives
- Structured and collaborative engineering culture
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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