Engineering Manager, Data Platforms & Analytics

OpenKrill; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Virta Health seeks an Engineering Manager for Data Engineering to lead and grow the data foundations supporting care delivery and AI capabilities. You will oversee Data Engineers and Analytics Engineers, shaping the team's next growth phase, with responsibility for reliable pipelines, platform tooling, and engineering standards.

You will drive data modernization, expand self-service, and enable ML by using trusted data.

Qualifications

• 3+ years of engineering management experience leading data/analytics engineering teams.
• Strong judgment across data pipelines, cloud warehouses, SQL, data modeling, orchestration, and BI/semantic layers.
• Experience leading data platform or analytics migrations with data validation and stakeholder adoption.
• Ability to translate business needs into an achievable roadmap without a dedicated product manager.
• Track record of building reusable capabilities and enabling other teams.

Responsibilities

• Lead and grow both data engineering and analytics engineering teams; coach and plan career growth.
• Complete data/analytics migration including BigQuery medallion architecture and Looker Core rollout.
• Own discovery, prioritization, and delivery; build a focused roadmap with stakeholders.
• Expand self-service by building reusable ingestion and transformation patterns and standards.
• Guide analytics engineering quality with reusable dbt models and LookML; establish semantic definitions.

Skills

Team leadership

Data pipelines

Cloud data warehouses

SQL

Data modeling

BI/semantic layers

Stakeholder management

Communication

Tools

BigQuery

dbt Cloud

Looker/LookML

Job description

Virta Health seeks an Engineering Manager for Data Engineering to lead and grow the data foundations supporting care delivery and AI capabilities. You will oversee Data Engineers and Analytics Engineers, shaping the team's next growth phase, with responsibility for reliable pipelines, platform tooling, and engineering standards.

You will drive data modernization, expand self-service, and enable ML by using trusted data.