Arquiteto de Dados (Google Cloud Platform (GCP) e Databricks) Sênior

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Arquiteto de Dados (Google Cloud Platform (GCP) e Databricks) Sênior based in Brazil. This is a senior-level opportunity for a data architecture professional to design modern, scalable, and high-performance data platforms. You will lead the architecture and implementation of Lakehouse environments using Google Cloud Platform and Databricks. The role combines strategic architecture, hands-on technical expertise, data governance, security, and large-scale migration initiatives. You will serve as a key technical reference for Data Engineering and Data Science teams, helping guide complex decisions and establish sustainable standards. The position offers significant exposure to modern data technologies, cloud platforms, Data Mesh, and multicloud architectures. You will collaborate closely with business stakeholders to transform organizational needs into robust and scalable technical solutions. The environment values innovation, continuous learning, collaboration, and the responsible use of data to generate business impact. This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Arquiteto de Dados (Google Cloud Platform (GCP) e Databricks) Sênior based in Brazil. This is a senior-level opportunity for a data architecture professional to design modern, scalable, and high-performance data platforms. You will lead the architecture and implementation of Lakehouse environments using Google Cloud Platform and Databricks. The role combines strategic architecture, hands-on technical expertise, data governance, security, and large-scale migration initiatives. You will serve as a key technical reference for Data Engineering and Data Science teams, helping guide complex decisions and establish sustainable standards. The position offers significant exposure to modern data technologies, cloud platforms, Data Mesh, and multicloud architectures. You will collaborate closely with business stakeholders to transform organizational needs into robust and scalable technical solutions. The environment values innovation, continuous learning, collaboration, and the responsible use of data to generate business impact. Accountabilities: Lead the design, documentation, and implementation of modern and scalable data architectures, particularly Lakehouse environments built with Google Cloud Platform and Databricks. Drive complex data migration initiatives, including transitions from on-premise environments to the cloud and migrations between cloud platforms. Define standards and best practices for data ingestion, processing, and consumption, balancing performance, scalability, reliability, and infrastructure costs through FinOps principles. Establish and promote effective data modeling practices across dimensional, relational, and NoSQL approaches, as well as Medallion Architecture principles covering Bronze, Silver, and Gold layers. Define and strengthen Data Governance guidelines covering data quality, lineage, cataloging, security, access, and compliance with LGPD requirements. Act as a senior technical reference for Data Engineering and Data Science teams, supporting complex architectural decisions and solving challenging technical problems. Promote a strong data culture by mentoring junior professionals, sharing knowledge, and contributing to the continuous evolution of data engineering practices. Partner with business stakeholders and organizational leaders to translate business requirements into secure, scalable, and technically sound data solutions. Establish and improve data delivery practices, including CI/CD and DataOps processes, ensuring reliable and repeatable data platform operations. Requirements: More than 5 years of experience in scalable Data Governance, with the ability to create, implement, and disseminate sustainable governance processes and policies. More than 5 years of hands-on experience with the Google Cloud Platform ecosystem, with strong practical knowledge of BigQuery, Cloud Storage, Dataflow, Cloud Composer, and Dataplex. Deep understanding of data modeling concepts, Data Mesh principles, and architectures supporting distributed data ownership and multiple domains. Knowledge of data cataloging, knowledge management, and data-sharing platforms designed to enable secure information exchange across multiple domains. Experience with Apache Iceberg and Open Table Format concepts, including integration with Apache Spark and BigLake to support multicloud portability. Strong practical experience with Databricks, including Delta Lake, Unity Catalog, and cluster optimization. Proven experience leading structured and unstructured data migration projects and designing new data architectures from the ground up. Solid professional background as a Data Architect or Principal/Senior Data Engineer, with the technical maturity to lead architecture decisions. Advanced proficiency in PySpark, Python, and SQL for large-scale data processing and transformation. Experience with Lakehouse architecture and CI/CD pipelines for data environments, including DataOps practices. Excellent communication and stakeholder management skills, with the ability to translate complex technical concepts into clear business language and lead architectural discussions. Official GCP certifications, such as Professional Data Engineer or Professional Cloud Architect, are strong differentiators. Official Databricks certifications, such as Certified Data Engineer Professional or Solutions Architect, are also valued. Experience with Infrastructure as Code, particularly Terraform, and exposure to loyalty programs, e-commerce, payment services, or financial services are considered additional advantages. Availability to work remotely under a CLT employment model. Benefits: Fully remote work model, providing flexibility and autonomy in your professional routine. CLT employment structure with a comprehensive benefits package. Medical insurance with family coverage options, including spouse and children. Dental insurance with coverage for employees and eligible dependents. Profit Sharing and Results (PLR), recognizing individual and organizational contributions. Childcare assistance to support eligible parents and families. Meal and food allowances through Alelo. Home office allowance to support a comfortable and productive remote workspace. Partnerships with educational institutions offering discounts and incentives for courses and degree programs. Financial support and incentives for professional certifications, including cloud certifications across GCP, Azure, AWS, and other technologies. Points-based rewards program offering flexibility in how benefits and rewards are used. TotalPass access with discounted fitness plans for employees and family members. Mindfulness and meditation support focused on well-being and quality of life. Opportunities to work with modern Data, Cloud, AI, governance, and engineering technologies while continuously developing technical expertise. 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! Why Apply Through Jobgether? 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. #LI-CL1