Headspace is dedicated to providing lifelong mental health support through innovative technology and evidence-based content. The Staff Data Engineer will lead the development of a privacy-first data platform to enhance personalized care, while mentoring team members and shaping the company's data strategy.
Responsibilities:
- Lead the implementation of a resilient, privacy-first data platform architecture that powers personalization, ethical AI, and accelerates data-driven decisions
- Lead the design, infrastructure, and tooling decisions for platform optimization and consolidation efforts, including the deprecation of legacy and redundant tooling such as Appflow, Prefect, Stitch, Redshift, and Looker
- Develop AI-ready architecture by creating semantic layers that define and standardize business logic, enabling data for Agentic AI, and spearheading new support for ML, experimentation, and onboarding to experimentation pipelines like Statsig
- Mentor other members of the DE and broader data team, particularly around dbt architecture and query performance
- Foster a data-first culture that prioritizes excellence, innovation, and collaboration across teams
- Act as a technical thought leader, shaping the company’s data strategy and influencing cross-functional roadmaps with data-centric solutions
Requirements:
- 6+ years in data engineering, with extensive experience in data platform development, complex data model designing, and data compliance implementation
- Production experience writing performant Python and PySpark code on distributed compute (Spark 3+, Delta Lake)
- Existing experience with Databricks is preferred or experience with Redshift and/or Snowflake
- Demonstrated expertise in architectural patterns for building high-volume ETL pipelines
- Experience with data modeling, Medallion architecture, pipeline design, metrics calculation and technical documentation
- Exceptional oral and written communication abilities, facilitating effective cross-functional collaboration
- BA/BS degree in Computer Science, Engineering, or a related field, or equivalent practical experience
- Experience in developing AI-ready architecture, such as creating semantic layers that standardize business logic for Agentic AI enablement
- Exposure to event streaming (Kafka, EventHub) and CDC tools
- Experience in deployment and infrastructure management using Terraform is a plus
- Prior experience implementing governance, privacy, and security frameworks across a data platform
- Familiarity with the complexities of PII/PHI data, HIPAA, and biometrics data
- Experience migrating or working with DBT for transformations, documentation, and lineage tracking