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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 position focused on designing and scaling modern data platforms that power analytics, machine learning, and data-driven decision-making across global clients. You will act as a key architect of enterprise-grade data ecosystems, ensuring high performance, scalability, security, and reliability across complex data environments. Working in a highly collaborative and international setup, you will partner with data scientists, engineers, product teams, and business stakeholders to transform raw data into strategic business value. The role combines deep hands-on engineering with architectural leadership, requiring the ability to define standards, guide technical direction, and elevate engineering maturity across teams. You will also play a critical mentoring role, supporting engineers of varying seniority while shaping best practices across data engineering initiatives. This is a high-impact position where your decisions directly influence platform efficiency, data quality, and business outcomes at scale.
Accountabilities:
Design, build, and evolve large-scale, cloud-based data platforms that support analytics, machine learning, and business intelligence use cases
- Lead the development and optimization of scalable ETL/ELT pipelines for batch and near real-time data processing
- Define and implement data architecture standards, modeling approaches, and governance frameworks across projects
- Architect and maintain cloud-native data solutions using platforms such as AWS, Azure, or GCP
- Establish best practices for data quality, observability, monitoring, lineage, and security across data systems
- Collaborate closely with data scientists, analysts, and product teams to deliver reliable, production-ready datasets
- Lead technical discussions, conduct code reviews, and mentor data engineers across different levels of experience
Requirements:
8+ years of experience in data engineering, data architecture, or data platform roles, with exposure to enterprise-scale systems
- Strong expertise in SQL and advanced Python development for data processing and pipeline engineering
- Proven experience designing and implementing scalable ETL/ELT pipelines in cloud-based environments
- Deep knowledge of data modeling techniques such as Star Schema, Snowflake, or Data Vault
- Hands-on experience with orchestration tools such as Airflow, dbt, or equivalent technologies
- Strong experience with cloud platforms including AWS, Azure, or GCP, and modern data warehouse/lake architectures
- Solid understanding of CI/CD practices, data governance, security, and compliance standards
- Strong leadership, communication, and mentoring skills with the ability to influence technical decisions
- Advanced English proficiency for collaboration with international stakeholders
Benefits:
- Fully remote work with international project exposure
- Opportunity to work with global brands and high-growth startups
- Access to diverse and complex data engineering challenges across multiple industries
- Flexible work arrangements aligned with project needs
- Paid time off including birthday leave
- Learning and development support, including courses, certifications, and English classes
- Multicultural and collaborative work environment
- Participation in tech meetups, events, and knowledge-sharing initiatives
- Career growth opportunities across multiple technical and leadership paths
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