We are building an AI Center of Excellence and we are looking for a dynamic Analytics Engineering Manager (AI & Agentic Analytics) to be a player-coach to lead it from the inside. You will manage a team of analytics engineers, but you will also write code, design models, and ship LLM-powered automations that make different business and product functions measurably faster.
This is not a strategy-deck role. It's for someone intrinsically motivated by the question: *what should analytics look like when agents can query, reason, and act on our data?*
Responsibilities:
- Lead and mentor a high-performing team: Develop analytics engineers while remaining hands-on with code and design. Set best practices, foster collaborative code reviews, and create an environment where your team ships predictable, high-quality work.
- Ship AI that transforms how we work: Identify high-impact automation opportunities and bring them to life with LLMs. Build internal copilots, workflow agents, and intelligent data QA bots that measurably accelerate across different business and product teams. See your work directly impact the business.
- Own the semantic layer that powers everything: Design and maintain the metrics, entities, and metadata foundation in dbt and BigQuery that both analysts and AI agents rely on. Be the architect of a trusted, scalable data language that becomes the single source of truth across the organization.
- Make AI observable and continuously improve: Implement evaluation and monitoring frameworks using tools like Langfuse or Phoenix. Track quality, cost, latency, and drift in real-time, then close the loop with data-driven improvements. Build a culture of accountability and excellence.
- Build and maintain a rock-solid foundation: Own core ETL pipelines, warehouse modeling, and data quality on BigQuery. Keep the infrastructure reliable so your team can focus on innovation and impact.
- Partner strategically across the business: Collaborate directly with stakeholders across different business and product functions to translate complex challenges into elegant data solutions. Be the bridge between business needs and technical excellence.
- Stay pragmatic with technology: Build with our proven stack—dbt, BigQuery, LlamaIndex, ADK, and n8n—while thoughtfully evaluating new tools that add real value. Lead with both technical depth and business judgment.
Find out more about our Data and Analytics folks here:
- Turn insights into impact!
- Looking for a career in data analytics? This could be the opportunity for you!
- Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, or a related field.
- Around 5+ years in analytics engineering or data engineering with strong data modeling, ELT, and warehousing experience.
- Around 3+ years leadership or mentoring experience with analytics engineering teams