Senior Data Analytics Manager, HashiCorp

• Several years developing analytics from data to dashboard using tools like Tableau, Looker, Sigma in an enterprise SaaS environment
• Experience working with data from user behavior platforms like Segment, Heap, and Mixpanel
• Strong grasp of SQL, structuring data, and ability to effectively query multiple tables of different grains with the use of subqueries and window functions
• Excellent problem-solving analytical skills with the ability to synthesize and communicate complex results
• Ability to shape ambiguity into tangible deliverables
• Strong communication skills with an emphasis on written communication
• Experience presenting insights and recommendations to senior leaders
• Experience with stakeholder management and setting expectations
• Attention to detail
• Self-directed and inquisitive
• Explain complex ideas simply
• Ability to tell a story with data
• Ability to set and manage expectations

Desirable

• Product Analytics is focused on translating our trove of data into consumable models and tools that accelerate time-to-insight for the HashiCorp product organization
• As a Sr. Analytics Manager, you will work closely with Data Engineering and product teams to orchestrate pipelines that power your analyses and dashboards to enable actionable insights for your stakeholders
• You will make it easier for every PM and key business stakeholder at HashiCorp to reliably self-serve answers to their questions about customer behavior and product usage, by leveraging the wealth of customer and product data we generate
• This role is an individual contributor with both functional and technical responsibilities
• Deliver on inquisitive analyses that answer critical business questions
• Own the creation and maintenance of self-serve tools (data models, reports, dashboards, etc.) that will enable the PM organization to be more data-centric in their decision-making
• Engage deeply with the HashiCorp product teams to understand their critical user journeys and help drive the right data pipelines to capture those milestones
• Identify and drive opportunities to make data more consumable and decrease time-to-insight for analytics consumers