Engineering Manager, Data Engineering

Virta Health

. Lead and grow the data engineering and analytics engineering disciplines .

Posted 10/23/2026full-timeRemote • United StatesMid-LevelSenior💰 $175,000 - $228,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data engineering and analytics engineering teams, focusing on stakeholder engagement, roadmap prioritization, and the development of reusable data capabilities. Proficient in managing data migrations, ensuring data quality, and implementing AI-assisted workflows in a regulated environment.

Highest-signal resume keywords

Data Engineering ManagementAnalytics Engineering LeadershipBigQuery Medallion ArchitectureStakeholder Roadmap PrioritizationAI-Assisted Development Workflows

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data PipelinesCloud WarehousesSQLData ModelingTransformation FrameworksOrchestrationBI LayersData ValidationPerformance ManagementGoverned Datasets

Soft Skills

CoachingClear CommunicationCollaborationTechnical JudgmentStakeholder Engagement

Tools & Technologies

BigQueryDbt CloudLookerLookMLGCPPythonGoInfrastructure as Code

Industry Keywords

HealthcareSensitive-Data GovernanceAccess ControlsRegulated Industry

Tech Stack

Tools & technologies

BigQueryCloudGoogle Cloud PlatformPythonSQLGo

About the role

Key responsibilities & impact

Lead and grow the data engineering and analytics engineering disciplines
Coach engineers, set expectations, and support technical and career growth
Assess capability gaps and define profiles for additional hires
Complete the BigQuery medallion architecture and Looker Core migration
Lead validation, stakeholder onboarding, and retirement of legacy data paths
Build relationships with Engineering, Analytics, Finance, Commercial, and Clinical stakeholders
Translate stakeholder needs into a focused roadmap and resolve competing priorities
Expand self-service through reusable ingestion and transformation patterns, tooling, documentation, and standards
Guide reusable dbt models, shared semantic definitions, and LookML development
Build and operate data agents and enable governed datasets and semantic context for AI and ML workflows
Partner with Applied AI and MLOps on data access, quality, and interfaces
Establish ownership, testing, freshness expectations, alerts, and incident practices
Partner with Security and Infrastructure on access controls, PHI/PII protection, lineage, and cost management
Apply AI-assisted development and automation to reduce toil and improve delivery
Measure adoption, migration progress, reliability, and stakeholder feedback
Deliver migration or self-service milestones and align quarterly roadmap priorities

Requirements

What you’ll need

3+ years of engineering management experience
Direct leadership of both data engineering and analytics engineering work
Strong technical judgment across data pipelines, cloud warehouses, SQL, data modeling, transformation frameworks, orchestration, and BI or semantic layers
Experience leading a significant data platform or analytics migration, including data validation, stakeholder adoption, and operational continuity
Experience owning stakeholder discovery and roadmap prioritization without a dedicated product manager
Track record of building reusable capabilities and helping other teams adopt them
Experience hiring, coaching, and managing performance across different engineering skill sets
Experience building collaborative teams in a remote or asynchronous environment
Clear communication with technical and business audiences
Experience with BigQuery, dbt Cloud, Looker/LookML, GCP, Python, Go, or infrastructure as code is a bonus
Experience building data agents, governed natural-language analytics, semantic layers for AI, or data capabilities supporting production ML systems is a bonus
Experience introducing AI-assisted development workflows with effective testing and review practices is a bonus
Experience in healthcare or another regulated industry, including sensitive-data governance and access controls, is a bonus
Authorization to work in the United States

Benefits

Comp & perks

Remote-first work arrangement
Office hubs in Denver and San Francisco
Security and privacy training provided
AI-assisted development and automation opportunities
Location-based compensation structure
HIPAA, security, and privacy support procedures
Equal employment opportunity protections