Engenheiro de Dados - Databricks

Job description

Accountabilities: Develop, maintain, and evolve a corporate data platform using Databricks as a core technology. Design and optimize scalable, distributed data pipelines to support analytics and business use cases. Build data transformation and processing solutions using Apache Spark and cloud-based architectures. Integrate, transform, and expose data across multiple business areas in a reliable and efficient way. Support DataOps practices, including automation, monitoring, and observability of data pipelines. Work collaboratively in agile, cross-functional teams to deliver high-quality data solutions. Ensure engineering best practices, including version control, testing, and CI/CD pipelines. Contribute to architectural improvements and continuous evolution of the data platform. Requirements: Bachelor’s degree completed in Computer Science, Engineering, Data-related fields, or equivalent experience. Strong hands-on experience with Databricks and Apache Spark in production environments. Advanced knowledge of Python, SQL, and Scala for data engineering tasks. Experience with cloud environments, preferably Google Cloud Platform (GCP). Solid understanding of distributed data formats such as Delta Lake and Parquet. Experience with ETL/ELT tools and modern data integration practices. Familiarity with CI/CD pipelines and Git-based version control. Experience working in agile and collaborative environments. Knowledge of DBT (Data Build Tool) is highly desirable. Familiarity with Kubernetes and Terraform is a plus. Experience in data platform modernization projects or high-volume data environments is a strong advantage. Background in financial services or large-scale data systems is also a plus. Benefits: CLT employment contract. Fully remote work model. Meal or food allowance. Health and dental insurance coverage. Access to discounts on education, language courses, and universities. Internal learning platform with free, certified online courses. Mentorship programs to support professional growth. Discount programs for healthcare services and partner establishments. Travel club benefits and pet care partnerships. 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 This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Engineer – Databricks in Brazil. This role is focused on building and evolving a modern, scalable data platform within a high-impact financial environment. You will be responsible for designing and maintaining robust data pipelines that support analytics, engineering, and business decision-making across multiple domains. Working with cloud-native technologies and distributed data architectures, you will help shape the foundation of a next-generation data ecosystem. The position requires a strong hands-on profile, capable of delivering efficient and reliable data solutions using Databricks and Spark. You will collaborate closely with multidisciplinary teams in an agile environment, contributing to continuous improvement, automation, and data quality practices. This is a strategic opportunity to work on a large-scale platform modernization journey with significant technical depth and business impact.