Engineering Manager, Data Engineering

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead and enhance the disciplines of data engineering and analytics engineering.

• Mentor engineers, set clear expectations, and facilitate technical and career advancement.

• Evaluate capability gaps and outline profiles for new hires.

• Finalize the BigQuery medallion architecture and the Looker Core migration.

• Oversee validation, stakeholder onboarding, and the decommissioning of legacy data pathways.

• Cultivate relationships with Engineering, Analytics, Finance, Commercial, and Clinical stakeholders.

• Convert stakeholder requirements into a targeted roadmap and manage competing priorities.

• Enhance self-service capabilities through reusable ingestion and transformation patterns, tools, documentation, and standards.

• Direct reusable dbt models, shared semantic definitions, and LookML development.

• Construct and manage data agents while enabling governed datasets and semantic context for AI and ML workflows.

• Collaborate with Applied AI and MLOps on data accessibility, quality, and interfaces.

• Establish ownership, testing protocols, freshness expectations, alerts, and incident management practices.

• Work with Security and Infrastructure on access controls, PHI/PII protection, lineage, and cost management.

• Implement AI-assisted development and automation to minimize toil and enhance delivery.

• Track adoption, migration progress, reliability, and stakeholder feedback.

• Achieve migration or self-service milestones and align priorities for the quarterly roadmap.

⛳️ Requirements

• 3+ years of experience in engineering management.

• Direct leadership experience in both data engineering and analytics engineering.

• Strong technical judgment across data pipelines, cloud warehouses, SQL, data modeling, transformation frameworks, orchestration, and BI or semantic layers.

• Proven experience in leading significant data platform or analytics migrations, including data validation, stakeholder adoption, and operational continuity.

• Experience in owning stakeholder discovery and prioritizing roadmaps without a dedicated product manager.

• Proven track record of developing reusable capabilities and facilitating their adoption by other teams.

• Experience in hiring, mentoring, and managing performance across diverse engineering skill sets.

• Experience in building collaborative teams in remote or asynchronous settings.

• Ability to communicate clearly with both technical and business audiences.

• Familiarity with BigQuery, dbt Cloud, Looker/LookML, GCP, Python, Go, or infrastructure as code is advantageous.

• Experience in building data agents, governed natural-language analytics, semantic layers for AI, or data capabilities supporting production ML systems is a plus.

• Experience introducing AI-assisted development workflows with effective testing and review practices is a bonus.

• Background in healthcare or another regulated industry, including sensitive data governance and access controls, is a bonus.

• Authorization to work in the United States.

🏝️ Benefits

• Remote-first work environment.

• Office hubs located in Denver and San Francisco.

• Training in security and privacy provided.

• Opportunities for AI-assisted development and automation.

• Compensation structure based on location.

• Procedures for HIPAA, security, and privacy support.

• Equal employment opportunity protections.