Lead the evolution of a modern data architecture by shaping strategy, refining data models, and ensuring long-term scalability. In this role, you’ll transition a growing data ecosystem into a well-structured, reliable platform that supports both operational and analytical needs across the organization.
What You’ll Do
- Define and drive the long-term data roadmap, aligning architecture with business and product objectives.
- Design and refine complex data schemas for transactional and analytical systems, ensuring clarity and performance.
- Optimize database structures and queries to improve speed, reliability, and maintainability.
- Apply deep analytical insight to uncover key data patterns and guide strategic priorities.
- Establish consistent naming standards, governance practices, and architectural principles across the data landscape.
- Write Python scripts to automate data workflows, exploration, and system maintenance tasks.
- Collaborate with Product, Engineering, and business teams to ensure data models support real-world use cases and user experience.
What We’re Looking For
- Expert-level SQL skills, including advanced query logic, CTEs, window functions, and aggregations.
- Proven experience designing scalable data models across different operational contexts.
- Strong background in database performance tuning and structural optimization.
- Functional proficiency in Python for data scripting and automation.
- Strategic thinking with the ability to identify how data architecture influences business outcomes.
- Self-driven approach to managing complex systems and leading architectural change independently.
- Fluent English communication skills for effective collaboration with global stakeholders.
Nice-to-Have
- Hands-on experience with Snowflake or similar cloud data warehouses.
- Background in implementing data governance and metadata management frameworks.
- Experience optimizing ETL or ELT pipelines to reduce processing delays.
- Familiarity with modern data tools such as dbt or Airflow.
- Previous work in distributed teams across Latin American time zones.
