Senior Analytics Engineer | Partners

About the Role

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.

Your Impact

• Design, build, and maintain high-quality data pipelines and data models from scratch within a data mesh architecture, ensuring reliability, scalability, and clear ownership.
• Evolve existing data assets and processes, raising the bar on data standards, definitions, and governance within the Partners business area.
• Build AI-powered capabilities — data/AI agents, reusable skills, and natural-language interfaces — that amplify the team's productivity.
• Model and enrich our BI semantic layer (Looker/LookML preferred) so both humans and AI tools can reliably consume it.
• Partner with Data Analysts, Data Engineers, and business stakeholders to turn loosely defined needs into clear, well-scoped technical work.
• Communicate complex technical concepts and trade-offs clearly to non-technical audiences.
• Live the mission: inspire and empower others by genuinely caring for your own wellbeing and your colleagues. Bring wellbeing to the forefront of work, and create a supportive environment where everyone feels comfortable taking care of themselves, taking time off, and finding work-life wellness.

Who You Are

• 3-5+ years in analytics engineering, data engineering, or closely related fields, with strong hands-on experience in complex pipelines, data modeling, and data architecture.
• Excellent SQL and production-grade Python (automation pipelines, not just exploratory code).
• Strong command of the full data lifecycle; experience in a data mesh (or similarly decentralized) architecture is a strong plus.
• Hands-on experience with a semantic layer or BI modeling tool (LookML/Looker strongly preferred).
• Practical knowledge of AI/LLMs: how LLMs consume structured context, and experience designing context for AI agents (writing instructions, scoping boundaries, building agent capabilities).
• Strong autonomy and organization — thrives in unstructured, high-demand environments and prioritizes effectively.