Analytics Engineer - Especialista I (Diretoria de Dados) · [CONFIDENCIAL]

Accountabilities

• Lead data modeling and transformation:Design, build, and maintain robust data layers in Google BigQuery, translating complex business rules into clean, efficient, scalable, and version-controlled code.

• Conduct exploratory data analysis:Develop ad hoc analyses to investigate business and data-related issues, identify root causes, prevent data-related impacts on Data Science models, and generate actionable insights.

• Ensure data quality and governance:Implement automated data tests, quality monitoring, and technical documentation to maintain the reliability of critical business indicators and support compliance with Brazil’s General Data Protection Law (LGPD).

• Optimize performance and costs:Improve query performance and data pipelines, ensuring scalability for large data volumes while managing cloud processing costs effectively.

• Partner with business and product teams:Collaborate with Product Managers and business stakeholders to understand complex challenges, lead end-to-end discovery, and propose proactive architectural solutions, including semantic layers in Looker.

• Promote data-driven decision-making:Support self-service Business Intelligence (BI) by building accessible metrics and analytical layers that enable stakeholders to explore data and make informed decisions.

• Provide technical leadership and mentorship:Serve as a technical reference for the team through code reviews, pair programming, knowledge sharing, and the promotion of engineering best practices.

• Own delivery from discovery to production:Take responsibility for the full development lifecycle, including requirements gathering, critical analysis, solution design, documentation, implementation, validation, and production deployment.

• Challenge assumptions and solve root causes:Go beyond initial requests to identify underlying business problems, question assumptions, and deliver sustainable solutions rather than short-term fixes.

Requirements:

• End-to-end ownership and analytical thinking:Demonstrated ability to work autonomously and consultatively, leading initiatives from stakeholder discovery and technical refinement through documentation, development, validation, and production delivery.

• Advanced SQL and Google BigQuery:Strong practical experience transforming and querying data in BigQuery, with a solid understanding of query optimization, processing efficiency, cost management, and scalable data solutions.

• Python for data engineering:Proficiency in Python, particularly for developing and maintaining stored procedures (PROCs), alongside its application in exploratory data analysis and data problem-solving.

• Data modeling and semantic layers:Extensive experience refining source data, designing reliable data models, and building semantic layers that support business analysis, competitive insights, and the evaluation of analytical models.

• Looker and business intelligence:Strong hands-on experience with Looker, including the development of semantic and metrics layers, interactive dashboards, and reliable reporting solutions.

• Data quality, governance, and LGPD compliance:A rigorous approach to automated testing, data validation, documentation, governance, and the classification and protection of confidential and sensitive information. Experience reducing recurring data incidents is highly valuable.

• Workflow orchestration:Practical experience using Apache Airflow to orchestrate and manage data pipelines and workflows.

• Software engineering practices:Familiarity with Git-based version control, code reviews, collaborative development, and continuous integration and continuous delivery (CI/CD) pipelines.

• Communication and collaboration:Strong communication skills and the ability to work effectively with technical teams, Product Managers, and business stakeholders, translating complex needs into practical data solutions.

• Autonomy and critical thinking:A proactive, detail-oriented mindset, sound technical judgment, and the ability to challenge assumptions, investigate root causes, and manage priorities independently.

Benefits:

• Flexible medical and dental insurance plans.

• Medication assistance and health benefits for family members.

• Free psychotherapy sessions and 24-hour telemedicine access.

• Ongoing preventive healthcare, mental well-being, and vaccination programs.

• Meal vouchers or access to a local restaurant, plus food vouchers and an additional Christmas food allowance.

• Discounts of up to 40% across the partner company's brand ecosystem.

• Gympass/TotalPass access to gyms, fitness studios, and sports activities.

• Home office allowance for eligible hybrid and remote work arrangements.

• Birthday day off.

• Pet health insurance, partner discounts, and travel and accommodation programs.

• Extended parental leave, including up to 180 days for mothers and 120 days for fathers.

• Support for parents of children with additional needs, childcare assistance, and early childhood education support.

• School supply assistance and child nutrition credits.

• Dedicated legal, psychological, and social guidance.

• Private pension plan and life insurance.

• Bereavement support for the loss of parents and payroll-deductible loan options.

• Public transportation allowance and parking, depending on the work arrangement.