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LifeStance Health

Nationwide in-person and telehealth mental care

Principal Analytics Engineer

Data EngineeringPosted on Nov 3
Full-timeRemote in USARemote

About the Job

Requirements

  • A bachelor's degree in Data Analytics, Statistics, Computer Science, Engineering, Informatics, or another discipline with relevant work experience is required.
  • At least 10 years of experience using advanced SQL to build production-grade data transformations, analytical datasets, and reusable models supporting business intelligence, analytics, or data products.
  • At least 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.
  • At least 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 designing and executing analytics data models with dbt, including facts and dimensions, modularity, normalization and denormalization trade-offs, incremental processing, testing, lineage, and performance optimization.
  • 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.
  • Legally authorized to be employed in the United States.
  • Awareness, inclusivity, sensitivity, humility, and experience working with individuals from diverse ethnic backgrounds, socioeconomic statuses, sexual orientations, gender identities, and other aspects of culture.

Responsibilities

  • Architect, build, and maintain SQL-based data transformations that convert data from electronic health record 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 key performance indicators.
  • Establish analytics-engineering adoption foundations, including modeling patterns, development standards, testing practices, documentation expectations, code-review approaches, and repeatable pathways from analysis to governed production assets.
  • Develop and maintain datasets used by enterprise dashboards and analytical products in Power BI or similar tools to provide actionable insights and self-service capabilities for operational, functional, and executive stakeholders.
  • Partner 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.
  • Advise teams on analytics engineering, 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 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, electronic health record transition needs, and modernization of the data and analytics environment.

Desired Qualifications

  • Deep experience with cloud data platforms such as Snowflake, Redshift, or Databricks and modern transformation and software-development practices using dbt, Git, continuous integration and continuous delivery, automated testing, and orchestration tools.
  • Experience integrating electronic health record, scheduling, patient access, customer relationship management, workforce, finance, or revenue-cycle data to support enterprise key performance indicator reporting, patient journey analytics, capacity and utilization insights, retention analysis, or operational decision-making.
  • Experience leading analytics modernization, electronic health record or source-system transitions, semantic-layer development, data-product governance, or migration from report-specific logic to reusable governed models.
  • An 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.

About the Company

LifeStance Health

Nationwide in-person and telehealth mental care

LifeStance Health provides mental health care across the United States through a network of about 4,000 clinicians, including psychiatrists, psychologists, and licensed therapists. With more than 450 centers in 31 states, it offers both in-person and telehealth appointments, making care flexible and accessible. The company focuses on personalized care plans tailored to each client’s needs and accepts most insurance plans to keep services affordable. Core services include diagnosis, therapy, and medication management delivered by a team of qualified professionals who work with individuals, families, and groups. Compared with others in the space, LifeStance leverages a large nationwide footprint, a mixed delivery model (in-person and telehealth), and a commitment to individualized treatment plans to reach a broad audience efficiently. Its goal is to improve access to trusted, affordable, and personalized mental healthcare so people can lead healthier, more fulfilling lives.

Company size
5,001-10,000
Company stage
IPO
Headquarters
Bellevue, WA
Founded
2017

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