• Develop and implement Advanced Analytics, Machine Learning and Artificial Intelligence solutions aimed at solving business problems. • Translate the needs of partner areas into analytical models, data products and scalable solutions. • Design analytical architectures and data pipelines (ETL/ELT), ensuring quality, performance and governance. • Build, train, deploy and monitor predictive and prescriptive models, ensuring their continuous improvement. • Develop data- and AI-based products such as recommendation engines, segmentation, forecasting and intelligent automations. • Apply MLOps and DataOps practices to ensure versioning, deployment, monitoring and maintenance of models in production. • Serve as a technical reference within squads, supporting architectural decisions and promoting Analytics and AI best practices. • Contribute to the evolution of a data-driven culture by encouraging strategic use of data across the organization.

Role Description We are seeking a highly motivated Analytics Engineer to join our growing Data & Insights organization. In this role, you will partner closely with the Associate Director of Data Insights to build a curated semantic and reporting layer that serves as the trusted foundation for all business intelligence, reporting, and analytics solutions across internal teams and client-facing products. This role blends deep technical rigor with execution speed, ideal for someone who takes pride in building well-modeled, secure, and performant data foundations while also delivering analytics products that create immediate business value. You will work hands-on with modern embedded and enterprise BI tools, including Bold BI and Reveal BI, alongside cloud data platforms to deliver scalable, governed, and reusable analytics experiences. Qualifications - Semantic & Reporting Layer Development: Design and maintain a curated semantic layer that standardizes business metrics, definitions, and hierarchies ensuring consistent, governed, and reusable data access across all BI and analytics consumers. - Data Modeling: Build and optimize robust dimensional and analytical data models (star/snowflake schemas, aggregated layers) that support performant, scalable reporting across diverse use cases. - Performance Tuning: Identify and resolve query performance bottlenecks through indexing strategies, materialized views, query optimization, caching configurations, and push-down SQL techniques. - Security Implementation: Implement and enforce row-level security (RLS), role-based access control (RBAC), and data masking policies within the semantic layer and BI platforms to ensure data is accessed only by authorized users. - Collaboration: Partner with Product, Data Engineering, and Client Success teams to translate business requirements into production-ready data models and analytics deliverables. - Data Quality & Validation: Perform exploratory data analysis and validation to ensure accuracy, consistency, and trust in all published metrics and insights. - Documentation: Document semantic layer definitions, data models, security policies, and implementation patterns to support adoption, auditability, and long-term maintainability. - Dashboard & Report Development: Design and deliver dashboards, KPI scorecards, and embedded analytics using Bold BI, Reveal BI, and other enterprise BI tools, with a strong emphasis on speed to value and stakeholder adoption. Requirements - A well-structured, governed semantic layer serves as the single source of truth for all reporting and analytics consumers. - Data models are clean, performant, and extensible — reducing ad hoc rework and enabling faster future delivery. - Security policies are consistently enforced at the data layer, ensuring compliance and appropriate data access across user roles. - Dashboards and reports built in Bold BI and Reveal BI are scalable, reusable, and trusted by stakeholders. - Time-to-delivery decreases through standardization, reusable models, and template-driven builds. Benefits - Join a powerful tech workforce and help us change the world through technology. - Professional development opportunities with international customers. - Collaborative work environment. - Career path and mentorship programs that will lead to new levels. - Contribute to shaping the data landscape within a dynamic and growing organization. - Your skills will be honed, and your contributions will play a vital role in our continued success. - Lean Tech is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

• As a Senior Analytics Engineer within Wellhub's Partner Data & Insights team in Brazil, you'll sit at the intersection of data engineering, applied AI, and business analytics. • This is a highly autonomous, technically deep role focused on building and evolving the data foundations that power decision-making across our Partners business. • You'll design, build, and maintain robust data pipelines in a data mesh architecture, model our semantic/BI layer, and create AI-powered capabilities — like data/AI agents — that scale the impact of the whole team. • You'll work closely with analysts and stakeholders, translating vague, fast-moving needs into the reliable pipelines that feed our data assets, and bringing an analytical lens to the work when it helps. • You'll own technical work end-to-end, from ambiguous problem to production-grade solution.

• Design, build, and optimize complex Power BI semantic models, advanced DAX measures, and executive-grade dashboards • Develop and tune dbt models and SQL transformations against Snowflake and other modern cloud data platforms • Own end-to-end data pipelines that consolidate CRM, ERP, product, and financial data into trusted, reusable layers • Diagnose and resolve performance, accuracy, and usability issues in existing reporting independently • Establish and enforce semantic modeling patterns, KPI definitions, naming conventions, and code review practices • Mentor mid-level and junior analytics team members through pairing, review, and documentation • Partner with the Director to shape the analytics architecture and reduce technical debt over time • Champion governance and data quality controls without slowing the team down • Work directly with RevOps and FP&A stakeholders to define metrics, forecasting views, and performance frameworks • Translate evolving requirements into intuitive, high-quality visualizations leaders trust and use • Present findings clearly to technical and non-technical audiences alike