This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Analytics Tech Lead based in Brazil.
This role offers the opportunity to lead the evolution of data analytics capabilities within a fast-growing technology environment.
You will act as a bridge between business needs, customer challenges, and technical data solutions.
The position combines technical leadership, analytics expertise, and people development to drive impactful decisions.
You will guide a team of data analysts while ensuring high-quality dashboards, metrics, and insights.
Working closely with product and business teams, you will help transform complex data into actionable outcomes.
This is an opportunity for a senior analytics professional who enjoys solving problems, mentoring others, and building scalable data practices.
Accountabilities:
As a Data Analytics Tech Lead, you will be responsible for guiding the analytics team, improving data-driven decision-making, and ensuring technical excellence across data initiatives. You will collaborate with multiple stakeholders to translate business objectives into reliable metrics, analyses, and solutions.
- Evaluate and prioritize analytics demands with the data team, considering complexity, effort, business impact, and delivery expectations.
- Support communication between product teams and data analysts by ensuring alignment on scope, timelines, feasibility, and technical requirements.
- Provide technical guidance and mentorship to data analysts working on dashboards, analyses, and data layers.
- Conduct regular one-on-one meetings to support team development, performance tracking, and career growth.
- Act as a senior technical reference for the analytics team, supporting day-to-day decisions and problem-solving.
- Ensure customer needs are accurately translated into relevant metrics, KPIs, and analytical requirements.
- Review and guide complex exploratory and ad hoc analyses, including cohorts, funnels, segmentation, performance variations, and root cause investigations.
- Define and maintain standards for semantic layers, metric definitions, business rules, dimensions, and team documentation.
- Establish best practices for data visualization, analytical quality, and consistency across deliverables.
Requirements:
The ideal candidate is an experienced analytics professional with strong technical foundations, leadership capabilities, and the ability to connect technical solutions with business objectives.
- Solid experience with Python (including pandas, numpy, and notebooks) and SQL.
- Previous experience managing, mentoring, or leading data professionals or analytics teams.
- Ability to evaluate technical complexity, prioritize initiatives, and manage stakeholder expectations.
- Strong communication skills with the ability to explain technical concepts to both technical and business audiences.
- Knowledge of descriptive statistics and basic statistical inference concepts.
- Experience applying software engineering best practices, including Git version control, documentation, and code refactoring.
- Intermediate English proficiency.
- Experience applying AI tools and solutions to data workflows is a plus.
- Experience working with retail businesses, medium or large customers, or customer-facing analytics projects is a plus.
- Knowledge of dimensional modeling, semantic data layers, ETL/orchestration tools such as Airflow, and non-relational databases is desirable.
Benefits:
- Fully remote work model, providing flexibility to work from home.
- Contractor (PJ) engagement model.
- Flexible meal and food allowance of R$ 1,100 through a multi-purpose benefits card, also usable for mobility, culture, health, and education.
- Fully company-paid health insurance with no co-payment.
- Fully company-paid dental insurance with no co-payment.
- Access to wellness programs to support physical and mental health.
- Incentives focused on learning, reading, and continuous development.
- Opportunity to contribute to an innovative AI-driven platform transforming how organizations use data.
- Collaborative environment with opportunities for professional growth and impact.
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