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.