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# Lead Data Analyst

- **Company:** Parachute Health
- **Location:** United States
- **Experience:** Expert
- **Salary:** $160,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, BigQuery, Data Warehousing, Python (Programming Language), SQL Databases, Snowflake, Data Analytics, Looker Analytics, Amazon Redshift
- **Published:** September 24, 2026
- **Apply:** https://www.thejobnetwork.com/job/lead-data-analyst-509976316

## About the Role

* 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 semantic layer thinking.
 * Working knowledge of experimentation design and causal inference - enough to catch correlation being mistaken for causation.
 * Comfort collaborating with analytics engineers on data modeling and warehouse design., * You get up to speed on an unfamiliar part of the business quickly, and you'd rather serve ten stakeholders than one.
 * You operate well in ambiguity and move with urgency.

Comfort working with data adjacent to patient and healthcare information, and sound judgment about handling sensitive information, is a plus given our industry.

## Description

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., * You mentor without formal authority - people want your input because it's good, not because you outrank them.