This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an Analytics Engineer – Specialist I (Data Directorate) based in Brazil.
We are seeking an experienced Analytics Engineer to shape reliable, scalable, and well-governed data foundations that support strategic business decisions. In this specialist-level role, you will transform complex business requirements into high-quality data models, trusted metrics, and actionable insights. You will work across data engineering, analytics, and business teams, helping ensure data is accurate, accessible, secure, and cost-efficient. The role combines hands-on technical expertise with end-to-end ownership, from stakeholder discovery and solution design to production delivery. You will also help establish engineering best practices, strengthen data quality, and empower stakeholders through self-service analytics. This is an opportunity to influence data architecture, mentor colleagues, and drive meaningful business outcomes in a collaborative, technology-driven environment.
Accountabilities
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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.
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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.
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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).
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Optimize performance and costs: Improve query performance and data pipelines, ensuring scalability for large data volumes while managing cloud processing costs effectively.
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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.
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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.
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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.
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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.
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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:
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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.
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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.
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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.
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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.
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Looker and business intelligence: Strong hands-on experience with Looker, including the development of semantic and metrics layers, interactive dashboards, and reliable reporting solutions.
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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.
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Workflow orchestration: Practical experience using Apache Airflow to orchestrate and manage data pipelines and workflows.
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Software engineering practices: Familiarity with Git-based version control, code reviews, collaborative development, and continuous integration and continuous delivery (CI/CD) pipelines.
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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.
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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:
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Flexible medical and dental insurance plans.
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Medication assistance and health benefits for family members.
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Free psychotherapy sessions and 24-hour telemedicine access.
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Ongoing preventive healthcare, mental well-being, and vaccination programs.
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Meal vouchers or access to a local restaurant, plus food vouchers and an additional Christmas food allowance.
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Discounts of up to 40% across the partner company's brand ecosystem.
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Gympass/TotalPass access to gyms, fitness studios, and sports activities.
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Home office allowance for eligible hybrid and remote work arrangements.
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Birthday day off.
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Pet health insurance, partner discounts, and travel and accommodation programs.
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Extended parental leave, including up to 180 days for mothers and 120 days for fathers.
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Support for parents of children with additional needs, childcare assistance, and early childhood education support.
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School supply assistance and child nutrition credits.
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Dedicated legal, psychological, and social guidance.
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Private pension plan and life insurance.
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Bereavement support for the loss of parents and payroll-deductible loan options.
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Public transportation allowance and parking, depending on the work arrangement.