This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer (AI Data Platform) based in Brazil.
This is a hands-on opportunity for a Senior Data Engineer to optimize and strengthen a production-scale data platform supporting AI-powered products and business-critical applications. You will take ownership of complex data engineering challenges, from schema refactoring and migrations to pipeline reliability and warehouse optimization. The role focuses heavily on improving performance, scalability, data quality, and cost efficiency across the platform. You will work with modern technologies including Snowflake, dbt, Airflow, SQL, and Python within a structured Medallion Architecture. Success in this position means delivering measurable improvements that remain reliable under real production workloads. You’ll collaborate with architects and engineering peers while operating with significant autonomy and ownership. This is a 6-month temporary opportunity, with the possibility of extension.
Accountabilities:
- Refactor existing schemas and tables to eliminate duplication, improve consistency, and strengthen data structures across Bronze, Silver, and Gold layers.
- Execute safe, production-grade data migrations and schema changes while maintaining platform reliability and data integrity.
- Develop, maintain, and optimize dbt models, including incremental models, materializations, aggregations, and data quality tests.
- Refactor and optimize Airflow DAGs to improve pipeline reliability, efficiency, maintainability, and performance.
- Profile and tune Snowflake queries, including warehouse sizing, clustering, query optimization, and resource utilization.
- Implement aggregation and pre-computation strategies to improve dashboard performance and response times for data-driven and conversational applications.
- Improve overall warehouse scalability, efficiency, and cost-effectiveness through continuous optimization.
- Implement robust data quality testing and validation processes to identify and prevent issues before they reach production.
- Monitor, troubleshoot, and resolve production data issues, taking ownership of solutions through implementation and stabilization.
- Work with engineering and architecture teams to evaluate technical trade-offs and deliver maintainable, high-performance data solutions.
- Operate effectively within established architecture while bringing structure and reliability to undocumented or evolving pipelines and schemas.
- Follow Git-based development and CI/CD practices to safely deliver and maintain production data engineering changes.
Requirements
- 5+ years of professional experience as a Data Engineer working with production-scale data platforms.
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related discipline is preferred; equivalent professional experience may also be considered.
- Strong hands-on expertise with Snowflake, including query profiling, performance tuning, warehouse sizing, clustering, and cost optimization.
- Solid experience with dbt, including model design, incremental models, materializations, testing, and production optimization.
- Proven experience developing, refactoring, and operating Airflow DAGs in production environments.
- Advanced SQL skills with demonstrated experience diagnosing and resolving complex production performance issues.
- Working proficiency in Python for data engineering, automation, and platform tasks.
- Strong understanding and practical experience with Medallion Architecture and data consolidation or deduplication.
- Experience performing live schema refactoring and safe production data migrations.
- Hands-on experience with Git and CI/CD practices in production environments.
- Ability to work independently, take end-to-end ownership, and make sound technical decisions within an established architecture.
- Strong analytical and problem-solving skills, with a demonstrated focus on measurable performance and reliability improvements.
- Excellent communication skills and the ability to clearly explain technical decisions, trade-offs, and recommendations.
- Upper-Intermediate to Advanced English proficiency (B2+/C1) for technical collaboration and discussions.
- Nice-to-have experience includes Snowflake SnowPro or dbt Analytics Engineering certifications.
- Familiarity with data lineage and observability tools such as Monte Carlo, OpenLineage, or dbt Docs is advantageous.
- Exposure to BI or semantic-layer technologies, CDC or streaming pipelines, and data platforms supporting AI, LLM, or conversational products is a plus.
Benefits
- 6-month temporary contract with the possibility of extension.
- Opportunity to work on a modern, AI-oriented data platform supporting production-scale applications.
- Hands-on exposure to Snowflake, dbt, Airflow, Python, SQL, and modern data engineering practices.
- Significant autonomy and end-to-end ownership of technical solutions and production improvements.
- Opportunity to solve complex performance, scalability, reliability, and data-quality challenges.
- Collaboration with experienced engineering and architecture professionals in a technically focused environment.
- Opportunity to contribute to AI-native products and data platforms with meaningful business impact.
- Professional growth through exposure to modern cloud, data, and AI technologies.
- Collaborative culture focused on technical excellence, transparency, respect, and effective communication.
- Flexible working environment designed to support high-quality collaboration and focused engineering work.
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!
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.
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