Analytics Engineering Manager (AI & Agentic Analytics)

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.
• 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
• Advanced proficiency in SQL and Python.
• Experience in designing, developing, and rollout large scale automation / data driven solutions with proven impact (LLM solution a plus).
• Hands-on expertise with dbt and BigQuery (or equivalent platforms such as Snowflake or Redshift)
• Familiar with semantic layers, metrics frameworks, and metadata management.
• Excellent project management capabilities, including technical discovery, scope definition, resource planning, and progress tracking.
• Clear communicator who can explain tradeoffs to non-technical partners.

Benefits

Additional Information

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?*

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