Manager, People Analytics

The Workplace Engineering function sits at the intersection of traditional HR analytics and modern Product Engineering. We transform raw workforce data into a suite of "People Products" that drive high performance. We don’t just "report" on what happened; we engineer the tools and insights that determine what happens next.

This new role will report directly to the Global Head of Workplace Engineering, and sits within our Data discipline inside of our People department. Experienced data professionals at Canonical live at the intersection of software, data, and the business. They don't just help surface analytic artifacts; they help transform them into a strategic asset that elevates decision making and innovation across our global operations (e.g., sales, marketing, engineering, and human resources). They balance technical precision with business pragmatism, designing and iterating on experiments, automations, and products that transform insights into valued outcomes. They shape tomorrow's AI/Data stack in open source, ensuring that Canonical remains at the forefront of data-driven excellence. Their curiosity is contagious and has an amplifying effect on data literacy and stewardship across the business teams they support.

Location: This is a remote role based in the AMER or EMEA Region.

• Multi-Disciplinary Leadership:  Lead and mentor a specialized squad of People Data Scientists, Software Engineers, and UX Designers. You aren't just managing analysts; you are leading a product squad.
• Product Ownership on People Science: Bridge the gap between "HR-speak" and "Dev-speak", ensuring engineers understand the human behavioral intent behind the code.
• Strategic Insight & Business Outcomes: Move beyond descriptive metrics (e.g., turnover rate) to predictive and prescriptive insights (e.g., predicting attrition risk based on "Time-Product" engagement data).
• Data Stewardship & Product Storytelling: Act as the "Translator-in-Chief". Take complex data models and turn them into compelling narratives. Lead the development of AI Agents that can surface insights to managers in real-time. Ensure the "People Data Stack" is secure, GDPR/privacy-compliant, and acts as a "Single Source of Truth" across all People related offerings, products and services.
• “Effectiveness at Work” Strategy: Identify opportunities to leverage “High Tech” solutions in our People offerings, and free up more time for “High Touch”, human involvement, thereby maximizing human value.

• Background in data science, mathematics, or engineering, skilled in advanced statistics, data wrangling/science, databases (SQL, etc.) or software engineering.
• Strength in coding/scripting languages (Python, R, JavaScript, etc.), software engineering, visualization (e.g. Superset, Tableau), and automation.
• Ability to translate business questions to key research objectives.
• Ability to identify the best methodology to execute research, synthesize and analyze findings.
• Proven ability to lead and drive others to execute against well planned roadmaps, with a strong mentor/coaching mindset. 
• Willingness to examine the status quo and be resilient in the face of challenges.
• Ambition to build tomorrow's AI/Data stack in open source.
• An exceptional academic track record from high school and university.
• Business level written and spoken English.
• Sincere personal motivation aligned with our mission.
• International travel 2-4 times a year for company events up to two weeks long.

In addition we expect that you will match our values, by being:

• Precise, taking care to deliver correctness and clarity.
• Reliable, delivering high quality work that builds trust and confidence.
• Accessible, collaborating to build products and systems that are usable.
• Adroit, blending enthusiasm, knowledge, adaptability, style and character.

• Experience with dbt (Data Build Tool), Airbyte, Ranger, Superset, Temporal, or Trino
• Basic understanding of containerization technologies such as Docker and Kubernetes
• Agentic Engineering
• Product management
• User experience and design

We consider geographical location, experience, and performance in shaping compensation worldwide. We assess performance and revisit compensation twice annually to ensure we recognize outstanding colleagues. In addition to base pay, we offer a performance-driven annual bonus or commission. We provide all team members with additional benefits which reflect our values and ideals. We balance our programs to meet local needs and ensure fairness globally.

• Distributed work environment with twice-yearly team sprints in person
• Personal learning and development budget of USD 2,000 per year
• Bi-annual compensation review
• Company recognition rewards
• 40 days annual leave per annum, including public holidays and our All Company holiday periods
• Maternity and paternity leave
• Team Member Assistance Program & Wellness Platform
• Opportunity to travel to new locations to meet colleagues, with Priority Pass for lounge access

Canonical is a pioneering tech firm at the forefront of the global move to open source. Our platform, Ubuntu, is very widely used in breakthrough enterprise initiatives such as public cloud, data science, AI, engineering innovation, and IoT. Our customers include the world's leading public cloud and silicon providers, and industry leaders in many sectors. We are founder-led, profitable, and growing.

Powered by worldwide distributed collaboration since our inception in 2004, we believe tech and business leadership can emerge anywhere. We have no central headquarters. Most of us work from home, but we are exceptionally disciplined about this. We have very high expectations of all colleagues, and are champions of excellence. Working here is a step into the future and will challenge you to think differently, work smarter, learn new skills, and raise your game.

We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.