Huntress is seeking a Staff Data Analyst to partner with support and security operations leadership teams to transform complex data into actionable insights for customer journey mapping and to measure the health of customers and operations teams.
Requirements
- Advanced proficiency in SQL for data querying and manipulation.
- Proven experience with BI tools such as Sigma, Tableau, Looker, Power BI, or similar platforms.
- 5+ years of experience in data analytics, business intelligence, or a similar role, with a strong focus on customer health reporting, preferably within a B2B SaaS environment.
Responsibilities
- Own the analytical framework for measuring the health of our customers and support and security operations teams.
- Design, build, and maintain a suite of scalable dashboards and reports using business intelligence tools (e.g., Sigma, Tableau, Power BI, Looker) that provide visibility into performance.
- Conduct complex data analysis using SQL to extract, manipulate, and analyze data from various sources (e.g., Salesforce, marketing automation platforms, financial systems).
- Unlock value in our install base by leaning in with curiosity to investigate customer usage, enablement, and engagement.
- Offer insights into key performance indicators (KPIs) and provide timely alerts on significant changes, anomalies, or performance gaps.
- Proactively develop and present compelling, data-driven narratives to support strategic planning, investment decisions, and business reviews (e.g., QBRs, board meetings).
- Lead deep-dive analyses on critical business questions, such as sales motion effectiveness, market segmentation, and pricing strategy.
Other
- We are seeking a highly skilled and strategic Staff Data Analyst to be a key partner to our support and security operations leadership teams.
- This position requires a unique blend of technical expertise, business acumen, and the ability to clearly communicate a metric-driven narrative to a wide range of stakeholders.
- Serve as a trusted advisor by proactively identifying trends, opportunities, and risks within our customer health and support data products.
- Translate complex data concepts into clear, concise, and simple terms for non-technical audiences.
- Have regular meetings with key stakeholders that define what data product readiness looks like in the now, next, and future timelines.
