Data Analytics Team Lead

About the role

Connecteam, a platform for managing deskless teams, is looking for an AI-native Data Analytics Team Lead to lead its analytics team and shape how data drives business decisions. This is a hands-on leadership role combining people management, business understanding and technical leadership: you will lead and develop analysts, set technical and analytical standards, own the team's priorities and partner with stakeholders and senior leadership.

Key responsibilities

• Lead, manage and develop a team of Data Analysts, setting goals, giving feedback and supporting their growth.
• Own the team's priorities and analytical roadmap, focusing on the highest-impact business needs.
• Define technical and analytical standards across data modeling, SQL, dbt, testing, code reviews and BI.
• Partner with stakeholders and senior leadership to define KPIs and turn data into actionable recommendations.
• Lead high-impact analyses and guide the development of scalable data models and Looker dashboards.
• Ensure data quality, investigate anomalies and track issues and inconsistent metrics.
• Drive AI-native ways of working by automating repeatable analyses and processes.
• Stay hands-on with data, code and analysis on complex problems.

Required profile

• 5+ years in business, growth or data analytics within a fast-paced SaaS or web company, including 2+ years leading a team of Data Analysts.
• Strong business understanding and ability to turn business needs into clear analytical priorities.
• Technical leadership and experience establishing analytics and engineering best practices.
• Excellent communication and stakeholder-management skills with technical and non-technical teams.
• A proactive, hands-on approach and ability to prioritize in a fast-moving environment.

Required skills

• Advanced SQL and production experience with dbt, including data modeling, testing, lineage and CI.
• Git-based development and code review workflows.
• Dashboards in Looker or a comparable BI platform.
• Practical experience using AI agents in analytical or engineering workflows.
• Nice to have: governed semantic layer, Python, statistics, experimentation or A/B testing, B2B multi-tenant SaaS experience, and n8n, Cursor or internal data agents.