Lead Data Analyst
New
J
JobgetherHealth-tech, SaaS
Based in the United StatesFull-TimeLead
Salary$145,000–$175,000 annually
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLProduct AnalyticsStakeholder managementdbtDatabricksLookerR
Requirements
- 5+ years of experience as a Product Analyst, Customer Analyst, or in a similar analytical role.
- Demonstrated ownership of customer-facing initiatives and stakeholder relationships.
- Strong hands-on SQL expertise, ideally including experience with SQL transformations using dbt.
- Experience using Python or R for data analysis, including statistical analysis and interpretation.
- Experience with modern data stack technologies such as Databricks, dbt, and Looker.
- Proven ability to translate complex datasets into concise, actionable insights for executives and non-technical stakeholders.
- Experience designing measurement strategies for products or customer programs, including defining KPIs and instrumentation.
- Demonstrated ability to identify opportunities for long-term process improvements, data governance, and automation.
- Strong stakeholder management skills, with the ability to work effectively across Product, Engineering, Design, Sales, and Customer Success.
- Self-directed and comfortable working autonomously in ambiguous environments.
Responsibilities
- Define, develop, and own measurement frameworks for product initiatives, including success metrics, instrumentation, adoption, engagement, retention, and customer health.
- Identify opportunities to automate, scale, and improve recurring data processes, creating more efficient and reliable ways to meet stakeholder needs.
- Serve as a data subject-matter expert, helping internal teams understand and effectively use data while representing data priorities across the organization.
- Conduct analyses that deepen understanding of employee health and wellbeing trends, customer interests, user journeys, and product performance.
- Partner with Product Managers, Designers, and Engineers throughout the product lifecycle to ensure data informs discovery, prioritization, delivery, and evaluation.
- Collaborate with Customer Success and Sales to demonstrate product impact, develop customer-facing insights, and create compelling narratives for QBRs and executive reviews.
- Improve data governance, documentation, workflows, and reusable analytical assets to reduce complexity and improve consistency.
- Mentor and coach analysts, sharing technical expertise and helping raise the quality and impact of the analytics team.
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