Lead Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Engineer based in Brazil.

This role is a senior technical leadership position focused on designing and delivering scalable, high-performance data solutions for complex, data-driven environments. You will lead the development of robust data pipelines, ensuring reliable ingestion, transformation, and availability of data across enterprise systems. The position requires strong hands-on expertise in PySpark, SQL, and cloud-based data platforms, combined with the ability to collaborate across engineering, analytics, and product teams. You will play a key role in translating business requirements into scalable data architectures that support advanced analytics and machine learning initiatives. The environment is fast-paced, international, and highly collaborative, with a strong emphasis on ownership, quality, and continuous improvement. This is an opportunity to influence data strategy while remaining deeply technical and execution-focused.

• Lead the design, development, and optimization of scalable data pipelines using PySpark, Python, and SQL in distributed data environments.
• Build and maintain robust ETL/ELT processes and data warehousing solutions that ensure data accuracy, availability, and performance.
• Collaborate with machine learning engineers, analytics engineers, software developers, and product managers to translate business needs into technical solutions.
• Architect and implement data models and data processing frameworks across cloud platforms, ensuring scalability and reliability.
• Drive best practices in data engineering, including code quality, performance optimization, and system design.
• Support data migration, integration, and modernization efforts within cloud ecosystems such as Azure or similar platforms.
• Monitor, troubleshoot, and improve data pipelines to ensure high availability and operational efficiency.
• Contribute to the definition of data governance, documentation standards, and engineering processes.
• Provide technical leadership and mentorship to junior and mid-level data engineers.

Requirements:

• 8+ years of experience in data engineering or related roles within data-intensive environments.
• At least 3+ years of hands-on experience developing data pipelines using PySpark and Python.
• Strong expertise in SQL and data warehousing concepts, including ETL/ELT methodologies.
• Proven experience working with cross-functional teams including ML engineers, software engineers, and product teams.
• Advanced English proficiency (B2–C1/C2 level, both written and spoken) is mandatory.
• Strong problem-solving mindset with the ability to work independently in fast-paced, dynamic environments.
• Experience with cloud platforms, especially Azure services such as ADLS, Azure Data Factory, Synapse, or Azure SQL is highly desirable.
• Familiarity with tools such as Databricks, Event Hub, Cosmos DB, or similar technologies is a plus.
• Knowledge of CI/CD, DevOps practices, and data migration methodologies is an advantage.
• Experience with BI tools such as Power BI or SAP HANA is considered a bonus.
• Must be based in Central or South America (remote nearshore requirement).

Benefits:

• 100% remote, full-time contractor position with a U.S.-based client.
• Long-term engagement with renewable yearly contracts based on performance.
• Opportunity to work on large-scale, enterprise-grade data platforms.
• Exposure to modern cloud technologies and advanced data engineering ecosystems.
• Collaborative international environment with strong technical challenges and growth opportunities.
• Professional development potential within a high-impact, engineering-driven team.