Engenheiro de Dados (GCP/Databricks)

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

This role is focused on building robust, scalable, and high-performance data solutions that directly support strategic decision-making across the organization. You will work in a modern cloud environment, leveraging GCP and Databricks to design and maintain end-to-end data pipelines. The position involves handling complex data workflows, from ingestion to transformation and delivery, ensuring reliability, quality, and governance. You will collaborate closely with analytics, BI, and data science teams to enable data-driven insights. The environment is highly collaborative and innovation-oriented, with a strong focus on cloud architecture and engineering excellence. This is an opportunity to contribute to impactful data products in a dynamic, growth-driven consulting context.

Accountabilities:

• Design, develop, and maintain scalable ETL/ELT pipelines across cloud environments, ensuring performance, reliability, and maintainability.
• Build and optimize data processing solutions using Databricks (Spark/PySpark) for large-scale distributed workloads.
• Work on ingestion, transformation, and availability of data using Google Cloud Platform services such as BigQuery, Cloud Storage, and Dataflow.
• Design and evolve data architectures including Data Lake, Data Warehouse, and Lakehouse models.
• Integrate diverse data sources such as APIs, relational databases, and streaming systems.
• Ensure data quality, governance, security, and compliance across all data pipelines and datasets.
• Monitor and optimize system performance and cloud resource usage to improve efficiency and reduce costs.
• Collaborate with BI, Analytics, and Data Science teams to enable data-driven decision-making.

Requirements:

• Minimum of 4 years of experience as a Data Engineer working with large-scale data systems.
• Strong hands-on experience with Google Cloud Platform, including BigQuery, Cloud Storage, and Dataflow.
• Solid experience with Databricks and Apache Spark (PySpark) for distributed data processing.
• Advanced knowledge of Python and SQL for data engineering tasks.
• Experience in data modeling, including relational and dimensional modeling approaches.
• Experience with orchestration tools such as Airflow or similar workflow management systems.
• Familiarity with Git and modern version control practices.
• Experience with Delta Lake, streaming technologies (Kafka or Pub/Sub), and infrastructure as code (Terraform) is a plus.
• Knowledge of Docker, BI tools (Power BI, Looker, Tableau), and data governance practices is considered a strong differentiator.
• Intermediate or advanced English level is a plus.
• Strong analytical thinking, problem-solving skills, and ability to work in collaborative, agile environments.

Benefits:

• 100% remote work model.
• Opportunity to work with modern data stack technologies in cloud environments.
• Exposure to large-scale data projects involving analytics, AI, and cloud transformation.
• Professional growth in a highly experienced and multidisciplinary technology team.
• Collaborative and innovation-driven culture focused on continuous learning.
• Participation in impactful projects across data, cloud, and AI ecosystems.
• Access to complex and challenging engineering problems in enterprise-scale environments.

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