Job Summary: We are seeking Data Engineers to design, develop, and maintain scalable data pipelines on Microsoft Azure, promoting technical excellence and continuous learning. Key Highlights: 1. Design and develop scalable data pipelines on Microsoft Azure 2. Define and evolve DataOps and MLOps standards 3. Mentorship and technical development of Data Engineers We are inspired by tech powered by people. Therefore, we need individuals passionate about challenges and eager for continuous learning. We seek new makers to dream with us, who see beyond the obvious and are ready to join us on this journey of transformation and growth. We are expanding our horizons and looking for people who share this same passion for technology and continuous learning. If you fit this profile, join our team! ### **RESPONSIBILITIES AND ATTRIBUTES** * Design, develop, refactor, and maintain scalable data pipelines on Microsoft Azure using SQL, Azure Data Factory, Azure Synapse, Databricks, Python, and PySpark, meeting requirements for reporting, advanced analytics, and data science; * Define, disseminate, and evolve DataOps and MLOps standards, best practices, and frameworks, promoting automation, reliability, and continuous improvement in data ecosystem performance; * Architect and implement fault-tolerant mechanisms, observability, and performance optimizations, ensuring high quality, availability, and efficiency of data pipelines; * Conduct root cause analysis (RCA) and resolve complex incidents, applying strong analytical and technical capabilities to optimize data flows, improve SLAs, and reduce operational costs; * Collaborate with business stakeholders to understand needs, translate requirements into data solutions, and jointly lead delivery teams; * Actively mentor and provide technical development for Data Engineers at various seniority levels, fostering professional growth and technical excellence within the team. ### **REQUIREMENTS AND QUALIFICATIONS** * Advanced experience with cloud-based data platforms, with strong expertise in Microsoft Azure, including SQL, Azure Data Factory, Azure Synapse, Databricks, Python, PySpark, as well as SAP Datasphere, Power BI, or equivalent technologies; * Advanced experience with Azure DevOps, GitHub, and CI/CD practices applied to data pipelines, infrastructure, and automations; * Solid experience in data storage architectures, covering cloud environments, relational databases, mainframe systems, data lakes, and data warehouses; * Advanced experience building and orchestrating cloud-based ETL/ELT pipelines using code and/or ETL tools, with integrations to databases, APIs, and structured/unstructured files; * Proficiency in data warehousing concepts, data modeling, and agile methodologies applied to analytical solution development; * Advanced experience designing and developing large-scale data transformations and manipulations, applying distributed processing techniques to extract value from large volumes of heterogeneous data; * Proven ability to propose and present conceptual and technical improvements, influencing architectural and strategic decisions alongside technical teams and business stakeholders; * Strong commitment to continuous learning, with ongoing updates in data engineering, emerging technologies, and business context understanding; * Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, or an equivalent combination of academic background and professional experience in data engineering; * Fluent English, with the ability to communicate technically and commercially in global environments.