This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engenheiro de Dados GCP Sênior based in Brazil.
This is an opportunity for a senior data professional to design, build, and operate scalable data solutions in a large-scale corporate environment.
You will work across multiple business areas, combining new solution development with the operational support of production environments.
The role focuses on Google Cloud Platform, with strong involvement in data pipelines, governance, architecture, and analytics enablement.
You will contribute to complex data migrations and greenfield platforms while ensuring reliability, quality, security, and scalability.
The position requires someone comfortable moving between engineering and incident resolution, prioritizing critical issues without losing sight of ongoing deliveries.
Collaboration is central to the role, with frequent interaction across software engineering, business teams, and other technical stakeholders.
This remote opportunity is ideal for a technically strong professional who brings operational maturity, leadership, and a strong sense of urgency to challenging data environments.
Accountabilities
- Design and develop automated ETL/ELT pipelines to ingest data from multiple business areas and systems into Google Cloud Platform.
- Implement and maintain Medallion Architecture patterns across Bronze, Silver, and Gold data layers.
- Build and maintain governed views within BigQuery’s Analytics layer, ensuring data integrity, quality, and usability for downstream consumers.
- Support data governance initiatives and contribute to reliable, scalable, and secure data architecture.
- Operate within a Build & Run model, balancing the development of new solutions with the support and maintenance of production environments.
- Monitor, investigate, and resolve production incidents with a strong sense of urgency and prioritization, particularly when there is potential impact on end users.
- Provide workarounds and coordinate the appropriate technical teams when critical incidents require broader intervention.
- Collaborate closely with software engineering teams and business stakeholders to translate requirements into scalable technical solutions.
- Ensure data solutions follow established architecture, security, governance, and engineering standards.
- Provide technical leadership and help coordinate stakeholders when complex issues or competing priorities arise.
Requirements
- At least 6 years of total professional experience in Data Engineering.
- At least 4 years of hands-on experience with Google Cloud Platform in real production environments.
- Strong practical expertise with GCP services including BigQuery, Cloud Functions, Cloud Composer/Airflow, and Dataplex.
- At least 3 years of experience with data architecture at scale, including Medallion Architecture.
- Proven experience with complex data migrations or greenfield data platform development in large-scale environments.
- Advanced proficiency in SQL and Python for processing and manipulating large volumes of data.
- At least 2 years of practical experience working in Build & Run or similar operational models.
- Strong ability to assess production incidents quickly, prioritize issues based on business and customer impact, and respond effectively under pressure.
- Senior-level technical maturity and confidence in leading data solutions end to end.
- Strong stakeholder management skills, with the ability to collaborate simultaneously with analysts, software engineers, and business teams.
- Ability to manage competing priorities and conflicting requirements while maintaining clear communication and composure.
- Strong business acumen and ability to translate requirements from different business areas into scalable technical solutions.
- Google Cloud certifications, such as Professional Data Engineer or equivalent, are considered a plus.
- Experience with audit or risk-management tools such as TeamMate is considered a plus.
- Knowledge of CI/CD practices applied to data engineering and DataOps is an advantage.
Benefits
- Remote work model.
- Initial 6-month project, with possibility of extension.
- Medical insurance, including the possibility of coverage for spouses and children.
- Dental insurance, including dependent coverage.
- Profit-sharing program (PLR).
- Childcare assistance.
- Food and meal allowances through Alelo.
- Home-office allowance.
- Partnerships with educational institutions and discounts on courses and degrees.
- Financial incentives for professional certifications, including GCP, Azure, AWS, and other cloud technologies.
- Livelo points program.
- TotalPass fitness benefit for employees and eligible family members.
- Mindfulness and meditation program focused on well-being and quality of life.
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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