Principal Analytics Engineer

LifeStance Health

. Architect, build, and maintain SQL-based data transformations converting EHR and enterprise-system data into clean, tested, analysis-ready datasets .

Posted 11/3/2026full-timeRemote • United StatesLead💰 $160,000 - $175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in SQL-based data transformations and analytics engineering, with a strong focus on building scalable data models and ensuring data quality in healthcare environments. Proven ability to lead teams, mentor analysts, and establish standards for analytics practices and governance.

Highest-signal resume keywords

Advanced SQL ProficiencyAnalytics Data Model DesignCloud Data Platforms (Snowflake, Redshift, Databricks)EHR Integration and Analytics ModernizationData Governance and Privacy Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQL-Based Data TransformationsDimensional ModelingAnalytics EngineeringData Quality AssuranceMetric GovernanceTesting and DocumentationPerformance OptimizationData Product DevelopmentRoot-Cause AnalysisVersion-Controlled Development

Soft Skills

MentoringCollaborationProblem-SolvingInfluencing Without AuthorityCommunication

Tools & Technologies

Power BIDbtGitCI/CDAutomated TestingOrchestration Tools

Industry Keywords

Healthcare AnalyticsData PrivacySecurity ComplianceGovernance RequirementsEnterprise KPI Reporting

Tech Stack

Tools & technologies

Amazon RedshiftCloudSnowflakeSQL

About the role

Key responsibilities & impact

Architect, build, and maintain SQL-based data transformations converting EHR and enterprise-system data into clean, tested, analysis-ready datasets
Lead reusable enterprise data models and semantic layers for patient demand and conversion, engagement and retention, clinician capacity and productivity, scheduling and access, and priority KPIs
Establish analytics engineering adoption foundations, including modeling patterns, development standards, testing, documentation, code review, and pathways from analysis to governed production assets
Develop and maintain datasets for enterprise dashboards and analytical products in Power BI or similar tools
Partner with business leaders, data analysts, product teams, and subject matter experts to translate ambiguous questions into metric definitions, scalable data products, and decision-ready insights
Advise teams on model design, metric governance, source-of-truth decisions, data quality, performance, and responsibilities across data engineering, analytics engineering, and BI/reporting
Mentor data analysts in SQL, dimensional modeling, version-controlled development, testing, documentation, and reuse of governed data assets
Lead troubleshooting and root-cause analysis for complex data-quality and metric-consistency issues, implementing durable controls for trust, lineage, and maintainability
Collaborate with data engineering, platform, governance, and analytics teams on enterprise architecture, privacy and security requirements, EHR transitions, and modernization

Requirements

What you’ll need

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
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 (preferred)

Benefits

Comp & perks

Medical insurance
Dental insurance
Vision insurance
AD&D insurance
Short- and long-term disability insurance
Life insurance
401k retirement savings with employer match
Paid parental leave
Paid time off
Holiday pay
Employee Assistance Program
Competitive bonus plan