Senior Integration Analyst

About LifeStance Health

Role overview

Key responsibilities

• Lead data analysis across source systems, identify quality risks, establish integration standards, and define mappings for trusted data assets.
• Resolve complex cross-system relationships and grain challenges through lineage documentation, transformation requirements, root-cause analysis, and remediation recommendations.
• Own Silver Medallion source-to-target mappings for NPI, taxonomy, licensure, credentialing, payer enrollment, practice affiliation, and employment attributes across enterprise systems.
• Maintain Snowflake Horizon Catalog definitions, lineage, mappings, quality standards, ownership assignments, and critical data element documentation.
• Help establish business acceptance criteria for enterprise data products before production release.
• Lead validation and certification of critical identifiers and key elements in Silver layer datasets; identify defects and drive remediation with Data Engineering and DataOps.
• Manage Silver Medallion and reference data integration issues from intake and prioritization through impact assessment, remediation guidance, and resolution validation.
• Investigate data quality and integration trends across registration, scheduling, provider onboarding, credentialing, HR, and other operational workflows; define corrective actions.

Compensation

• Compensation is $120,000–$147,000 annually, in addition to a competitive bonus plan.

Benefits

• Full-time employee benefits include medical, dental, vision, AD&D, short- and long-term disability, and life insurance.
• Additional benefits include a 401(k) with employer match, paid parental leave, paid time off, holiday pay, and an Employee Assistance Program.

Requirements

• Independently lead enterprise data integration analysis initiatives across multiple source systems.
• Define source-to-target mapping strategies and complex data transformation requirements.
• Provide architectural direction for Silver Medallion layer design principles.
• Steward metadata and governance assets, including business definitions, data lineage, quality standards, ownership, and critical data element documentation.
• Analyze complex cross-system relationships and data grain, document lineage, conduct root-cause assessments, and recommend remediation approaches.
• Work effectively with business and technical stakeholders and Data Engineering and DataOps teams.