Job Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Engenheiro de Dados (GCP/Databricks) Especialista in Brazil.

This role is designed for a senior data engineering professional who will take ownership of scalable, cloud-native data architectures in a high-impact, innovation-driven environment. You will lead the design and evolution of modern data platforms, combining GCP services and Databricks to build robust lakehouse and analytics ecosystems. The position involves working with large-scale distributed systems, optimizing data pipelines, and ensuring performance, governance, and cost efficiency across environments. You will act as a technical reference for data engineering practices, guiding teams and shaping architectural decisions. In close collaboration with analytics, BI, and data science teams, you will enable reliable and high-quality data delivery across the organization. This is a strategic, hands-on role for someone passionate about building advanced data platforms that directly support business intelligence and AI initiatives.

Accountabilities:

• Lead the design and evolution of modern data architectures, including Data Lake, Data Warehouse, and Lakehouse models.
• Develop, optimize, and maintain scalable ETL/ELT pipelines for batch and streaming data processing.
• Act as a technical reference for data engineering teams, providing guidance on architecture, coding standards, and best practices.
• Design and implement distributed data processing solutions using Databricks, Spark, and PySpark.
• Define and enforce DataOps practices, including testing, CI/CD, versioning, and deployment automation.
• Ensure data governance, security, quality, and reliability across all data pipelines and platforms.
• Optimize performance and cost efficiency within Google Cloud Platform environments.
• Integrate multiple data sources and support real-time and batch data ingestion strategies.
• Collaborate with BI, Analytics, and Data Science teams to ensure data availability and usability.
• Participate in strategic decisions regarding data architecture, tooling, and platform evolution.

Requirements:

• Minimum of 5+ years of experience as a Data Engineer in large-scale environments.
• Strong hands-on experience with Google Cloud Platform (BigQuery, Dataflow, Cloud Storage, Pub/Sub).
• Advanced experience with Databricks, Apache Spark, and PySpark.
• Proficiency in Python and SQL for data engineering and processing tasks.
• Solid experience with data modeling (relational, dimensional, and Lakehouse architectures).
• Experience with orchestration tools such as Airflow or Cloud Composer.
• Strong understanding of CI/CD practices, Git version control, and modern engineering workflows.
• Experience working with large-scale, distributed data systems.
• Nice to have: experience with Delta Lake, Terraform, Docker, Kubernetes, Kafka, and data streaming architectures.
• Additional advantages include certifications in GCP or Databricks, experience with BI tools (Looker, Power BI, Tableau), and knowledge of data governance, LGPD, and observability practices.
• Strong communication skills and experience collaborating with technical and business stakeholders.
• English proficiency (intermediate to advanced) is a plus.
• Previous experience leading technical teams or data projects is highly valued.

Benefits:

• 100% remote work model with flexibility.
• Opportunity to work in a highly specialized and experienced data and AI consulting environment.
• Exposure to large-scale cloud and Databricks-based architectures.
• Collaborative and multidisciplinary engineering culture focused on innovation.
• Professional development in Data Engineering, Cloud, and AI domains.
• Access to complex, high-impact projects across multiple industries.
• Environment that values continuous learning, technical excellence, and knowledge sharing.

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