Staff Data Engineer

Role overview

The Staff Data Engineer at Headspace will build and evolve a privacy-first data platform that powers personalization, experimentation, and AI-ready capabilities. The role is foundational and staff-level, combining technical leadership, architecture ownership, and mentoring across the data team.

What you will do

• Lead implementation of a resilient, privacy-first data platform architecture for personalization, ethical AI, and data-driven decision-making
• Design platform optimization and consolidation initiatives, including deprecating legacy/redundant tooling (e.g., Appflow, Prefect, Stitch, Redshift, Looker)
• Build AI-ready architecture using semantic layers to standardize business logic for Agentic AI
• Enable and extend support for ML, experimentation, and onboarding to experimentation pipelines (e.g., Statsig)
• Mentor members of the DE and broader data team, especially on dbt architecture and query performance
• Promote a data-first culture across teams
• Act as a technical thought leader shaping Headspace’s data strategy and influencing cross-functional roadmaps

What you will bring

Required skills

• 6+ years of data engineering experience, including data platform development, complex data modeling, and data compliance
• Production experience writing performant Python and PySpark for distributed compute (Spark 3+, Delta Lake)
• Existing experience with Databricks preferred (or experience with Redshift and/or Snowflake)
• Expertise in architectural patterns for high-volume ETL pipelines
• Experience with data modeling and Medallion architecture; pipeline design; metrics calculation; technical documentation
• Strong oral and written communication for cross-functional collaboration

Preferred skills

• Experience building AI-ready architecture (semantic layers for Agentic AI enablement)
• Exposure to event streaming (Kafka, EventHub) and CDC tools
• Terraform experience (deployment/infrastructure management) is a plus
• Experience with data governance, privacy, and security frameworks
• Familiarity with PII/PHI, HIPAA, and biometrics data
• Experience migrating/working with dbt for transformations, documentation, and lineage tracking

Location & work model

• Remote in the US (must permanently reside in the US)
• Based in these cities; candidates in the greater SF area follow a hybrid model: 3 days/week in office, remote for the rest of the week (details shared by recruiter)

Compensation

• Base salary range (full-time): $140,400 – $224,250 + equity + benefits