Talent pool - SR Data Engineering - Hybrid/Remote

Role Summary

• At Inmetrics, innovation and excellence operate side by side in a collaborative, healthy and dynamic work environment. Our culture values:
• 📚 Constant learning
• 🗣️ Transparency in communication
• 🔄 Flexibility for continuous development

Our team is passionate about technology and committed to delivering real value to customers. Inmetrics' differentiator is digital efficiency.

💛 People are our greatest asset, which is why we invest in opportunities that go beyond competitive salaries, offering differentiated benefits and a healthy environment, recognized by our employees.

👉 #VemPraInmetrics

Technical and Strategic Leadership

Lead data engineering initiatives for on-premises and Cloud systems.

Act as a technical reference in the design, architecture and implementation of robust data solutions.

Quality, Security and Data Governance

Ensure the quality, integrity and security of data during all migration, transformation and storage processes.

Apply good practices in Data Governance, monitoring and auditing of data.

Collaboration and Business Understanding

Work in partnership with business teams, data scientists and analysts, translating needs into efficient analytical solutions.

Support the design of data strategies that promote insights and data-driven decision making.

Responsibilities

Our Talent Pool connects Senior professionals and Experts — to our opportunities focused on data engineering.

Pipeline Development and Optimization

• Design, develop and optimize ETL/ELT pipelines, ensuring high performance, scalability and reliability.
• Implement large-scale data processing solutions.

Requirements

Documentation and Continuous Improvement

• Develop and maintain technical and process documentation, ensuring traceability and reproducibility of implemented solutions.
• Contribute to the continuous evolution of the architecture and technical standards of the Data Engineering team.

Position Requirements

• Completed degree in Computer Science, Software Engineering or related field.
• Proven experience with Azure Data Lake, Databricks or similar technologies
• Proficiency in programming languages such as Python, Scala and SQL.
• Solid experience with ETL/ELT tools and distributed data processing frameworks.
• Advanced knowledge of relational and NoSQL databases, such as SQL Server and MongoDB.

Experience with data orchestration tools

• Familiarity with DevOps and CI/CD practices, applied to data pipelines.
• Knowledge of data governance, LGPD and good information security practices.

Complementary / Differential Requirements

• Knowledge of streaming architectures and real-time data processing.
• Experience in migrating data from legacy systems to cloud environments.
• Certifications focused on cloud data engineering.
• Experience in multicloud environments (Azure, AWS, GCP).