Data Insights Engineering Manager
hace 3 días
Your mission, should you choose to accept it:
- Lead and grow a Data Insights team
- Lead and coach 5–10 data professionals (e.g. Data Analysts, Senior Data Analysts, Analytics Engineers) within the Data Insights area, ensuring they are set up for success and have clear development paths aligned with our career frameworks.
- Create an environment of psychological safety, high performance, and ownership, where people are empowered to take initiative and learn.Own delivery and impact of insights work
- Take end‑to‑end responsibility for the planning and delivery of your team's roadmap, ensuring work is sliced for iterative delivery and focused on high‑impact outcomes for product and business stakeholders.
- Partner with Product Managers, Engineering Managers and business leaders to translate strategy and problems into clear analytical questions, projects and dashboards that drive decisions (not just reports).
- Elevate analytics quality and standards
- Ensure your team builds trustworthy, well‑documented and self‑serve analytics assets (dashboards, reporting, semantic models) using our modern data stack (e.g. Databricks, dbt, Looker, GoodData, Azure).
- Champion data quality, governance and consistency of metrics across domains; work closely with Data Engineering and Analytics Engineering on contracts, lineage and testing.
- Partner deeply with product & business
- Embed your team in one or more product tribes (e.g. Guest Experience / FinTech) as the analytical partner: defining KPIs, running deep‑dive analyses, designing experiments, and shaping product strategy with data.
- Ensure your team routinely engages with stakeholders, understands customer and user journeys, and uses both qualitative and quantitative insights to influence roadmaps.
- Build and improve ways of working
- Continuously improve how the team works: estimation, prioritisation, incident/bug handling, stakeholder communication, and documentation; align with broader Product & Engineering practices.
- Collaborate with other Data and R&D leaders to standardise best practices for discovery, delivery, and measurement of impact of data products and insights.
- 3–5+ years of experience in a data‑focused role (e.g. Data Analyst, Analytics Engineer, Data Scientist) and 2+ years managing or leading data teams (formal or informal people leadership).
- Proven experience leading multi‑disciplinary or cross‑functional teams, coaching individuals at different levels, and running performance and development cycles using a career framework or rubric.
- Solid hands‑on experience with analytics in a modern data stack: SQL as a must, plus familiarity with tools such as Python / PySpark, dbt, BI / visualization tools (e.g. Looker, GoodData), and cloud data platforms (e.g. Azure, Databricks).
- Ability to review analytical approaches, query logic, dashboards and data models for quality, performance and correctness, and to challenge your team to maintain high standards
- Experience working closely with product teams and/or business stakeholders, turning vague problems into sharp analytical questions and actionable recommendations.
- Comfortable making data‑informed decisions and helping others weigh trade‑offs between speed, complexity and value.
- Excellent written and verbal communication skills; able to explain complex analytical concepts to non‑technical stakeholders and tell clear stories with data.
- Strong collaboration skills; you enjoy building relationships across Product, Engineering, Finance, Operations, and other teams to align on goals and deliver results.
- Eager to help us change the world of hospitality with better data and better decisions.
- Curious, pragmatic, resilient, and comfortable operating in a fast‑moving, high‑growth environment where not everything is defined yet.
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