We're looking for a Senior Analytics Engineer to join our data team at PandaDoc. In this role, you'll be at the intersection of data engineering and analytics, building the foundational data models and infrastructure that power insights across the organization. You'll work closely with data analysts, business stakeholders, and engineering teams to transform raw data into trusted, accessible datasets that drive strategic decisions around customer success, revenue growth, and product development.
About the PandaDoc Data Platform:
You'll be working with a best-in-class modern data stack that reflects industry-leading practices. Our infrastructure is built on Snowflake as our cloud data warehouse, with dbt powering our transformation layer and Select Star providing comprehensive data cataloging and discovery. We've implemented robust data governance practices including PII auditing and data quality monitoring via Monte Carlo. Our platform integrates data from across the business—including Salesforce, HubSpot, Recurly, and our product databases—creating a unified view of customer journeys, subscription metrics, and product usage. We're actively exploring cutting-edge technologies like composable CDPs, reverse ETL with Hightouch, and event analytics with PostHog. The data team has a strong partnership with business stakeholders, regularly delivering high-impact analyses that drive decisions around customer expansion, payment gateway adoption, and product strategy. You'll have the autonomy to influence our architecture decisions and help shape our evolution toward an AI-enabled, domain-oriented data organization.
What You'll Do:
Design, build, and maintain dimensional data models in Snowflake that serve as the foundation for analytics and reporting across the company
Develop and optimize dbt models to transform raw data from systems like Salesforce, HubSpot, Recurly, and other business platforms into clean, reliable datasets
Create and maintain data documentation in Select Star and other catalog tools to ensure discoverability and understanding of our data assets
Partner with data analysts and business teams to understand their analytical needs and translate them into scalable data solutions
Implement data quality checks and monitoring to ensure accuracy and reliability of analytics datasets
Optimize SQL queries and data pipelines for performance and cost efficiency
Support strategic analytics initiatives including customer journey analysis, revenue analytics, and product usage metrics
Contribute to data governance practices including data quality standards, PII handling, and metadata management
Mentor junior team members and promote best practices in data modeling and analytics engineering
What You'll Bring:
5+ years of experience in analytics engineering, data engineering, or similar data-focused role
Expert-level SQL skills with experience writing complex queries, CTEs, and window functions
Strong experience with dbt (data build tool) for building and maintaining transformation pipelines
Hands-on experience with Snowflake or other cloud data warehouses (e.g. BigQuery, Redshift)
Familiarity with data cataloging tools (Select Star preferred)
Knowledge of data orchestration tools (Airflow / MWAA preferred)
Strong background in Python for data analysis or automation
Deep understanding of dimensional modeling, data warehouse design patterns, and analytics best practices
Experience working with SaaS metrics (MRR, churn, customer lifetime value, etc.)
Proficiency with GitHub for version control and collaborative development
Strong communication skills with ability to translate technical concepts for business stakeholders
Self-directed and comfortable working in a remote environment with distributed teams
Nice to Have:
Experience with reverse ETL tools such as Hightouch
Some exposure to BI tools (Hex preferred)
Understanding of data mesh or domain-oriented data architecture concepts
Company Overview:
PandaDoc empowers more than 60,000 growing organizations to thrive by taking the work out of document workflow. PandaDoc provides an all-in-one document workflow automation platform that helps fast scaling teams accelerate the ability to create, manage, and sign digital documents including proposals, quotes, contracts, and more. For more information, please visit https://www.pandadoc.com.
Company Culture:
We're known for our work-life balance, kind co-workers, & creative virtual team-bonding events. And although our Pandas are located across the globe, we stay connected with the help of technology and ensure that everyone on our team feels, well, like a team.
Pandas work best when they're happy. We retain our talent by upholding our values of integrity & transparency, and selling a product that changes the lives of our customers.
Check out our LinkedIn to learn more.
Benefits:
Employees may be able to purchase company stock (or receive annual bonuses)
Employees (and their families) may enroll in the company's medical, dental, vision, short & long term disability, life insurance, FSA and 401k plans.
Employees will also receive 13.34+ hours of paid time off per month, 6 self care days, birthday PTO day, and 12 company paid holidays off per year.
The annual base salary for this role is up to $140,000-$160,000.
PandaDoc is an Equal Opportunity Employer. We are committed to equal treatment of all employees without regard to race, national origin, religion, gender, age, sexual orientation, veteran status, physical or mental disability or other basis protected by law.
EXTERNAL RECRUITERS
Approval Requirement
The use of external recruiters/staffing agencies requires prior approval from our HR Team. The HR Team at PandaDoc requests that external recruiters/staffing agencies not to contact PandaDoc employees directly in an attempt to present candidates. Complying with this request will be a factor in determining future professional relationships with PandaDoc.
Application deadline: 2/28/26