Data Analytics Manager, HashiCorp

• Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent experience)
• 5+ years of experience in analytics, analytics engineering, business intelligence, data engineering or a related field
• Demonstrates the ability to write clean, performant and scalable SQL
• Hands-on experience with data modeling tools like DBT or similar frameworks, modern datawarehouse systems like Snowflake or Redshift for structuring and transforming data into high-quality usable models
• Experience building intuitive and impactful dashboards in one or more BI tools (e.g., Tableau, Sigma, Looker)
• Excellent problem-solving analytical skills with the ability to synthesize and communicate complex results
• Ability to shape ambiguity into tangible deliverables
• Strong communication skills presenting insights and recommendations to stakeholders and senior leaders

Desirable

• This is an individual contributor role responsible for hands-on development with both functional and technical responsibilities
• Marketing Analytics team is focused on translating key business data into consumable data models and tools that accelerate time-to-insight for the Hashicorp Marketing organization and Leadership teams
• As a Data Analytics Manager, you will work closely with the subject-matter experts from Product Marketing, Product PM’s, Revenue Marketing, Sales, Finance and IT teams to develop data models that power common marketing use cases, powering ad hoc analyses, reports/dashboards
• You will make it easier for key business stakeholders at HashiCorp to be able to self-serve answers to their questions leveraging the wealth of information around customer and product telemetry
• Own the creation and maintenance of well-structured and robust data models, dashboards and reports that enable business stakeholders to drive data-informed decisions
• Build and maintain reverse ETL workflows to business systems such as Marketo to support marketing campaigns
• Collaborate with cross-functional teams to define and track key business metrics tied to adoption, pipeline, revenue, product telemetry and customer success
• Identify and drive opportunities to make data more consumable and decrease time-to-insight for analytics consumers
• Develop documentation, training and enablement content to ramp users on models and dashboards for self-serve analysis