Senior AI Analytics Engineer

About Wellhub

At Wellhub we're revolutionizing workplace wellness. Our platform connects employees worldwide to the best partners for fitness, mindfulness, therapy, nutrition, and sleep—all in one simple subscription. Headquartered in NYC with team members in Europe, North America and South America, we’re on a mission to make every company a wellness company. We believe work should be fulfilling, inspiring, and balanced. Here, you’ll find a team that values wellbeing, collaboration, and different perspectives, where passion and creativity push boundaries to create real impact. Your contributions will help shape a healthier, more balanced world for you and millions of people globally.

The Opportunity

We are hiring a Senior AI Analytics Engineer to our Global Analytics team in Brasil - Remote! As a Senior AI Analytics Engineer within Wellhub's ever-growing Global Analytics team, you'll take a central role in driving a data-driven culture and executing on our analytics strategy. This technically focused role sits at the intersection of data modeling, software engineering, and applied AI — requiring deep hands-on skills across all three. You will be instrumental in building and maintaining the governed data foundations that power AI-driven analytics across the company, ensuring that every tool and workflow draws from consistent, trustworthy definitions of our most critical business concepts. This includes developing high-quality data models, building automated governance pipelines, and designing the context structures that make AI-powered self-serve analytics accurate and scalable at Wellhub. You will partner with teams across the product and business to translate complex and often loosely defined data needs into reliable, AI-ready assets that stakeholders can trust.

Your Impact

• Build and maintain high-quality LookML models, ensuring the semantic layer is enriched with accurate labels, descriptions, synonyms, and business logic that AI tools — including Looker Conversational Analytics and external LLMs — can reliably consume;
• Design and configure domain-focused Data Agents with well-structured instructions, Golden Queries, and scoped context governance to deliver accurate and trustworthy conversational analytics;
• Develop and maintain CI/CD pipelines that automate metadata governance, including AI-assisted description generation, DDL synchronization, and semantic consistency checks;
• Build reusable AI skills, tools, and workflows that allow analysts and stakeholders to interact with governed data through natural language interfaces;
• Partner with Data Analysts, Data Engineers, and business stakeholders to translate vague or poorly defined business questions into well-defined, measurable data models and agent instructions;
• Identify opportunities to improve the quality and reliability of AI-generated insights by improving context structure, metadata coverage, and semantic layer precision;
• Develop recommendations and drive improvements to data standards, processes, and definitions;
• Contribute to cross-team guidelines and best practices for responsible AI usage with data.

Who You Are

• 3-5+ years of relevant work experience in analytics engineering, data modeling, or a closely related field;
• Excellent SQL skills required;
• Proficiency in Python — comfortable writing and maintaining production-grade scripts and automation pipelines, not just exploratory code;
• Hands-on experience with a semantic layer or BI modeling tool (LookML/Looker, dbt Semantic Layer, or equivalent);
• Practical understanding of how Large Language Models consume structured context: field-level metadata, descriptions, synonyms, and prompt design;
• Experience designing context for AI agents: writing system instructions, scoping agent boundaries or contributing to agent skill frameworks;
• Experience building or maintaining CI/CD pipelines for data artifacts (GitHub Actions, dbt CI, or similar);
• Significant exposure to complex data pipelines, data modeling, and data architecture;
• Comfortable with AI-assisted development workflows: using AI coding tools, crafting Golden Queries, and building or configuring skills for data agents;
• Must be comfortable with unstructured, fast-moving, and constantly evolving high-growth environments;
• Strong execution and ownership — able to drive technical work end-to-end from ambiguous problem to reliable solution;
• Ability to communicate complex technical concepts clearly and concisely to non-technical stakeholders;
• Advanced English written and verbal communication skills.

We recognize that individuals approach job applications differently. We strongly encourage all aspiring applicants to go for it, even if they don't match the job description 100%. We welcome your application and will be delighted to explore if you could be a great fit for our team. For this specific role, please note that prior experience in Python, SQL and designing context for AI agents are mandatory requirements.