Contractor: Lead Analytics Engineer

Team: Analyst

Location: Brazil

Commitment: Contract

Workplace Type: remote

Accountabilities:

• Set the technical direction for the analytics team, including architecture, engineering conventions, and development approaches.
• Raise engineering standards through code reviews, design reviews, pairing, and consistent quality expectations.
• Own the architecture of data models with a focus on long-term maintainability, scalability, and reliability.
• Govern the semantic layer, metric definitions, and self-service analytics capabilities to help stakeholders access accurate information.
• Serve as the primary technical partner to Product, Finance, Marketing, and Engineering, translating business needs into an executable roadmap.
• Collaborate directly with stakeholders to negotiate scope, priorities, and delivery expectations.
• Establish a proactive analytics cadence that identifies important business questions and opportunities beyond incoming requests.
• Define the data testing strategy and ensure business logic is consistently validated across the analytics layer.
• Own the operational health of analytics systems, including monitoring, alerting, incident response, and release readiness.
• Mentor engineers, facilitate knowledge sharing, and build technical alignment through documentation and presentations.
• Lead large-scale data migrations and performance initiatives by setting the technical approach and enabling the team to execute successfully.

Requirements:

• 8+ years of professional experience working with data in a software engineering environment.
• Mastery of SQL and Python, with strong hands-on experience applying both to analytics engineering and data systems.
• Advanced experience with semantic layer tooling, data catalog platforms, and data integrity testing frameworks.
• Strong experience with dbt orchestration, development standards, and analytics engineering best practices.
• Proven ability to work autonomously and proactively, with deep expertise in data analysis and data systems.
• Experience with relational databases and DAG orchestration tools such as Dagster or Airflow.
• Hands-on experience with Tableau and modern analytics workflows.
• Experience with cloud infrastructure such as AWS or GCP, as well as infrastructure-as-code tools such as Terraform.
• Familiarity with document, graph, or schema-less data stores.
• Strong technical leadership and mentoring capabilities, with the ability to establish engineering standards and raise team-wide quality.
• Excellent stakeholder communication and collaboration skills, including the ability to translate complex technical concepts into practical business outcomes.

Benefits:

• Remote work.
• Opportunity to contribute to work that supports education and improves outcomes for students and teachers.
• Opportunity to shape analytics engineering architecture, standards, and technical direction.
• Long-term opportunity to lead high-impact data initiatives and mentor other engineers.