Principal Analytics Engineer

At LifeStance Health, we strive to help individuals, families, and communities with their mental health needs. Everywhere. Every day. It’s a lofty goal; we know. But we make it happen with the best team in mental healthcare.

Thank you for taking the time to explore a career with us. As the fastest growing mental health practice group in the country, now is the perfect time to join our team!

LifeStance Health Values

Belonging: We cultivate a space where everyone can show up as their authentic self.

Empathy: We seek out diverse perspectives and listen to learn without judgment.

Courage: We are all accountable for doing the right thing - even when it's hard - because we know it's worth it.

One Team: We realize our full potential when we work together towards our shared purpose.

• Benefits
• As a full-time employee of LifeStance Health, the following benefits are offered: medical, dental, vision, AD&D, short and long-term disability, and life insurance. Additional benefits include a 401k retirement savings with employer match, paid parental leave, paid time off, holiday pay and an Employee Assistance Program.

ROLE OVERVIEW

We are looking for an experienced Principal Analytics Engineer to provide technical leadership for Enterprise Analytics. Reporting directly to the VP of Analytics and Insights, this senior individual contributor will create the trusted, scalable analytics foundation used to understand enterprise performance and support better decisions across the organization. The role will design high-quality data models and analytics products spanning patient demand and conversion, access and scheduling, patient engagement and retention, operational optimization, enterprise KPIs, and major business transformation initiatives. You will remain hands-on with SQL, data modeling, testing, and documentation while serving as an internal expert who establishes standards, accelerates adoption of analytics engineering practices, and mentors data analysts as they incorporate those practices into their work.

Consistent with LifeStance’s values, every member of the LifeStance team is expected to support each other and the mission, which may mean participating in projects and initiatives and performing functions and responsibilities not specifically outlined in this job description.

COMPENSATION: $160,000 - $175,000/annually in addition to a competitive bonus plan

KEY RESPONSIBILITES

Architect, build, and maintain SQL-based data transformations that convert data from EHR and other enterprise systems into clean, tested, analysis-ready datasets with minimal technical direction

Lead the design of reusable enterprise data models and semantic layers that support consistent analysis of patient demand and conversion, patient engagement and retention, clinician capacity and productivity, scheduling and access, and other priority KPIs

Establish the foundation for analytics engineering adoption, including modeling patterns, development standards, testing practices, documentation expectations, code-review approaches, and repeatable pathways from analysis to governed production assets

Develop and maintain the datasets utilized by enterprise dashboards and analytical products in Power BI or similar tools that provide actionable insights and self-service capabilities for operational, functional, and executive stakeholders

Partner closely and iteratively with business leaders, data analysts, product teams, and subject matter experts to translate ambiguous questions into clear metric definitions, scalable data products, and decision-ready insights

Serve as an internal expert on analytics engineering, advising teams on model design, metric governance, source-of-truth decisions, data quality, performance, and the appropriate division of responsibilities across data engineering, analytics engineering, and business intelligence/reporting

Mentor data analysts in SQL, dimensional modeling, version-controlled development, testing, documentation, and reuse of governed data assets, helping analysts progressively adopt analytics engineering methods in day-to-day work

Lead troubleshooting and root-cause analysis for complex data quality and metric-consistency issues, and implement durable controls that improve trust, lineage, and maintainability across analytics products

Collaborate with data engineering, platform, governance, and analytics teams to align enterprise models with target architecture, privacy and security requirements, EHR transition needs, and modernization of the data and analytics environment

REQUIREMENTS

Bachelor’s degree in Data Analytics, Statistics, Computer Science, Engineering, Informatics, or another discipline with relevant work experience required

10+ years of experience using advanced SQL to build production-grade data transformations, analytical datasets, and reusable models supporting BI, analytics, or data products

8+ years of experience designing flexible, scalable analytics and data modeling solutions in healthcare environments, including dimensional models, semantic layers, and executive or operational dashboards

6+ years of experience operating independently in a senior or lead role, partnering with business and technical stakeholders to define metrics, resolve ambiguity, and deliver enterprise-scale analytics solutions

Demonstrated experience leading analytics engineering architecture and standards across complex, multi-data-source environments, with accountability for technical quality and long-term maintainability

Expert-level skills in analytics data model design and execution with dbt, including facts and dimensions, modularity, normalization and denormalization trade-offs, incremental processing, testing, lineage, and performance optimization

Proven ability to create adoption foundations and influence ways of working through standards, reusable frameworks, enablement, code review, documentation, and mentoring without relying on direct authority

Strong healthcare or similarly complex regulated-industry experience, with working knowledge of data privacy, security, minimum-necessary access, de-identification, and governance requirements

• •Qualified candidates must be legally authorized to be employed in the United States
• •LifeStance is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability, or any other legally protected status.
• •Demonstrates awareness, inclusivity, sensitivity, humility, and experience in working with individuals from diverse ethnic backgrounds, socioeconomic statuses, sexual orientations, gender identities, and other various aspects of culture.

PREFERRED SKILLS AND KNOWLEDGE

Deep experience with cloud data platforms such as Snowflake, Redshift, or Databricks and modern transformation and software-development practices using dbt, Git, CI/CD, automated testing, and orchestration tools

Experience integrating EHR, scheduling, patient access, CRM, workforce, finance, or revenue-cycle data to support enterprise KPI reporting, patient journey analytics, capacity and utilization insights, retention analysis, or operational decision-making

Experience leading analytics modernization, EHR or source-system transitions, semantic-layer development, data product governance, or migration from report-specific logic to reusable governed models

Advanced degree in Data Science, Analytics, Computer Science, Informatics, Engineering, or a related field, and experience coaching analysts or analytics engineers through formal or informal technical leadership

PHYSICAL REQUIREMENTS

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of the job. Reasonable accommodation may be made to enable individuals with