Engineering Manager, Data Engineering

About this role

Virta Health is seeking an Engineering Manager for Data Engineering to lead and grow a team responsible for data foundations that support the company’s care delivery, analytics, and AI capabilities. The role oversees both Data Engineers and Analytics Engineers, focusing on reliable pipelines, platform tooling, and reusable analytical models and Looker experiences. The manager will drive data and analytics modernization, expand self-service, and enable ML initiatives with trusted data, using BigQuery, dbt Cloud and Looker LookML. The position involves collaborating with multiple stakeholders to prioritise work and measure adoption. Location is not stated, with a remote-first setup and offices in Denver and San Francisco. The compensation range is $175,000 to $228,000, and security/privacy training is provided due to HIPAA considerations.”

What you would do

• Lead and develop both data engineering and analytics engineering teams.
• Assess team needs and plan hires to achieve the right mix of capabilities.
• Oversee the data and analytics migration, including validation and stakeholder onboarding.
• Own discovery, priorities, and delivery by engaging with Engineering, Analytics, Finance, Commercial, and Clinical teams.
• Expand self-service by building reusable ingestion and transformation patterns, tooling, and standards.
• Ensure quality of analytics engineering through reusable dbt models, semantic definitions, and LookML.
• Advance data capabilities for agents and ML, including data agents and governed datasets.
• Improve reliability and governance with ownership, testing, alerts, and incident practices; manage access controls and cost.
• Improve team workflows with AI-assisted development and automation while ensuring data correctness.
• Balance roadmap with operational support and measure impact through adoption and stakeholder feedback.

What they are asking for

• 3+ years of engineering management experience overseeing both data engineering and analytics engineering work.
• Strong judgment across data pipelines, cloud warehouses, SQL, data modelling, and BI or semantic layers.
• Experience leading a major data platform or analytics migration with data validation and stakeholder adoption.
• Experience guiding discovery and roadmap prioritisation without a dedicated product manager.
• Track record of building reusable capabilities and enabling other teams to adopt them.
• Experience hiring, coaching, and managing performance in a remote or asynchronous environment.
• Clear communication with technical and business audiences and ability to link priorities to company outcomes.

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