Data Analytics Manager

Job description

Ashby is hiring its first Data Analytics Manager for a full-time remote role in the United States. The manager will lead a team of three Data Analysts and help shape how Ashby's Data function scales as the company grows across products, regions, business systems, and internal data needs. This is a player-coach role that combines people leadership with hands-on analytical work, data modeling, business partnership, and AI-enabled analytics strategy.

Responsibilities

• Manage and develop Ashby's Data Analysts
• including coaching
• performance support
• hiring
• and team growth.
• Improve analytical practices for prioritization, review, knowledge sharing, quality, and collaboration.
• Help the Data team evolve from broad shared context toward stronger domain specialization without creating disconnected silos.
• Guide the team through the changing role of AI in analytics, self-service data access, internal business-data usage, and trusted warehouse-derived data.
• Remain hands-on with analysis while learning the business and supporting difficult analytical problems.
• Help prioritize incoming analytical requests and distinguish quick-turn work from larger planned projects.
• Support full-stack analytics work spanning raw and modeled data, dbt models, metric definitions, deep analysis, dashboards, and internal data products.
• Partner directly with stakeholders across the company to understand business context and translate ambiguous questions into useful analytical work.
• Help hire future analysts and assess technical judgment, curiosity, communication, business context, and ownership.
• Strengthen Ashby's open and principled data culture while maintaining a high bar for analytical rigor and accuracy.

Requirements

• Exceptional analytical judgment and ability to calibrate the depth and rigor of analysis to the business decision at hand.
• Ability to produce and evaluate transparent, rigorous analysis with clear assumptions, caveats, data-cleaning steps, statistical considerations, and practical conclusions.
• Strong written and visual communication, including clear charts, tables, metric definitions, and analytical narratives.
• Deep hands-on SQL experience.
• Working fluency with dbt-style data modeling, cloud data warehouses, and business-intelligence tools.
• Experience leading, managing, or functionally acting as a manager for data practitioners in a high-growth company.
• Ability to coach, hire, develop, and amplify analytical talent.
• Product-manager-like instinct for identifying the core need behind requests and turning ambiguous questions into useful analytical work.
• Pragmatic and intellectually flexible approach that treats data as one input to good decision-making rather than the default answer to every question.
• Experience in a growth-stage, product-oriented technology company is strongly relevant.
• Comfort staying close to hands-on analytical work rather than operating only as a people manager.

Skills

• Data Analytics Leadership
• People Management
• Analytical Judgment
• SQL
• dbt
• Cloud Data Warehouses
• Business Intelligence
• Data Modeling
• Metric Definition
• Dashboard Development
• Data Visualization
• Statistical Analysis
• Data Storytelling
• Business Partnership
• Stakeholder Management
• Hiring and Coaching
• Team Development
• AI-Assisted Analytics
• Self-Service Analytics
• Data Governance
• Product Analytics
• Data Quality
• Prioritization