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.

Accountabilities:

• 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.

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