Lead Data Analyst

Parachute Health is transforming post-acute care as the leading digital ordering platform for medical equipment and supplies. We connect major health systems, health plans, and suppliers to help patients get the life-saving products they need at home. Since launching, we've connected 300,000+ clinicians and 3,000+ supplier locations across all 50 states and helped 15M+ patients. What started as a DME ePrescribing tool has become the order management platform of choice for home medical equipment.

Join our team and make a difference in patient care.

About the Role

The Lead Data Analyst is the senior individual contributor on our Data Analytics team — a Level IV role on our analytics ladder, with no direct reports. You lead through expertise: setting the analytical bar, mentoring analysts, and being the person leadership comes to when a question needs a real answer rather than a guess.

Data Analytics sits under Revenue Operations, but we're a central function that supports the entire organization — clinical operations, supplier performance, payor and network data, product, finance, and go-to-market. The work is broad by design. The core of the job is being an excellent analyst: taking an ambiguous question from any corner of the business, building a rigorous analysis, and delivering a conclusion people can act on. We're hiring for analytical strength and range, not depth in one domain.
Responsibilities
Analytical leadership

- Lead end-to-end analyses on high-stakes, often ambiguous questions — from framing the problem through recommendation and impact measurement.

- Design dashboards and reporting frameworks that let stakeholders answer their own routine questions without opening a ticket — and recognize when a dashboard is the wrong answer.

- Set the bar for analytical rigor, methodology, and documentation. By example and by reviewing others' work, not by mandate.

- Apply statistical methods, experimentation design, and causal inference where they sharpen a conclusion rather than decorate it.

- Move between business domains and be credible in each, rather than owning one.

- Partner with leadership to identify where data can drive efficiency, growth, and improve outcomes — including the questions nobody has asked yet.

Partnership with analytics engineering

- Work closely with analytics engineers on data modeling. You'll shape what gets built in the warehouse layer, not just consume it.

- Turn recurring analytical needs into durable models instead of one-off queries.

- Hold a high standard for canonical definitions — when two reports disagree, you're the one who finds out why.

Team contribution (not people management)

- Mentor analysts on technique and business judgment. You don't manage anyone — you're the person newer analysts learn from.

- Translate findings into clear, concise language for both technical and non-technical audiences. If a new hire couldn't repeat the takeaway back to you, it isn't ready to ship.

- Influence senior stakeholders, including being the one who says "the data doesn't support that" to someone who wanted a different answer.

What we're looking for
Experience

- 8+ years in data analysis, business intelligence, or a comparable analytical role, with a track record of insights that changed how a business made decisions.

- 2+ years operating at a senior analyst level — owning complex projects end-to-end and holding others to a quality standard.

- Experience supporting multiple business functions from a central analytics team.

- Bachelor's degree in a quantitative or technical field, or equivalent experience.

- Hands-on experience with modern cloud data warehouses (BigQuery, Snowflake, Redshift, or similar).

- Nice to have: exposure to revenue and go-to-market data — pipeline, forecasting, funnel, retention, CRM.

Technical skills

- Expert-level SQL. Strong Python for statistical work.

- Advanced Looker or comparable BI tool experience — LookML, dashboard design, and