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This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer (Databricks) | SR based in Brazil.
This senior-level role sits at the core of modern data-driven architecture, supporting the design, development, and evolution of scalable data platforms in a cloud environment. You will work with large-scale data pipelines and distributed processing systems, ensuring that data is reliable, accessible, and ready for advanced analytics and business decision-making. The position involves hands-on work with Azure, Databricks, PySpark, and SQL, as well as close collaboration with engineering teams to translate business needs into robust technical solutions. You will also play a key role in maintaining performance, stability, and security across data ecosystems. Beyond development, the role emphasizes operational excellence, including monitoring, automation, and continuous improvement of data workflows. This is a highly technical environment where data quality, resilience, and scalability are central to everything delivered.
Accountabilities:
- Collaborate with data engineering teams to understand business and technical requirements, translating them into efficient and scalable data solutions.
- Develop, maintain, and optimize data pipelines and platforms using Azure, Databricks (PySpark), Python, Data Lake architectures, and SQL.
- Implement data processing and transformation logic using Python, including Pandas for structured data analysis and ElementTree for XML manipulation and integration of heterogeneous data sources.
- Ensure system availability, stability, and performance by monitoring, troubleshooting, and continuously evolving data solutions in production environments.
- Support data security, governance, and compliance requirements through automation, proactive management, and continuous improvement practices.
- Implement data quality controls, testing frameworks, and monitoring strategies to ensure integrity and reliability of data assets.
- Maintain comprehensive technical documentation for developed processes, architectures, and solutions.
- Provide production support, including corrective actions and change management (CHG) follow-up to ensure smooth operational delivery.
Requirements
- Solid experience with SQL (including regex usage), Databricks, PySpark, and Python for data engineering and analytics workflows.
- Strong knowledge of data manipulation techniques, especially text processing and regular expressions for complex data parsing.
- Experience with SQL data modeling and foundational understanding of distributed computing concepts.
- Hands-on experience working with Data Lake architectures and large-scale data environments.
- Ability to operate in high-responsibility production environments, including on-call availability after business hours and weekends when required.
- Strong problem-solving mindset, attention to detail, and ability to work in collaborative, fast-paced engineering teams.
- Experience with cloud data platforms (particularly Azure) and modern data engineering practices is highly valued.
Benefits
- Competitive compensation package aligned with senior-level expertise
- Opportunity to work on large-scale, cloud-native data platforms using cutting-edge technologies
- Exposure to advanced AI, data engineering, and digital transformation initiatives
- Flexible work arrangements depending on project and team structure
- Career development opportunities within a global, innovation-driven environment
- Access to modern tooling and AI-assisted engineering ecosystems
- Collaborative and highly technical work culture focused on continuous learning and impact.
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