Senior Data Engineer

Headspace exists to provide every person access to lifelong mental health support. As a Senior Data Engineer, you will help build the modern data platform that powers personalized, ethical, and scalable mental health support for millions of members by designing and implementing robust data pipelines and collaborating with analytics and data science teams.

Responsibilities:

• Contribute to architecture and implement robust data pipelines to ingest, aggregate, and index diverse data sources into the organization’s data lake
• Drive the creation of a secure, compliant, and privacy-focused data warehousing solution tailored to meet the healthcare industry’s stringent requirements
• Partner with the data analytics team to deliver a data platform that supports accurate, actionable reporting on key business metrics
• Collaborate with the data science and machine learning teams to build tools and capabilities that foster rapid experimentation and innovation
• Support peers and champion a culture that values data as a strategic asset across the organization

Requirements:

• 4+ years of proven success designing and implementing large-scale data systems
• Strong understanding of core python, its tooling (pip, poetry, popular frameworks like pytest or pydantic)
• Strong pyspark experience (dataframe API) and understanding of internal architecture and optimization techniques
• 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 modelling, 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 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
• Experience in developing AI-ready architecture, such as creating semantic layers that standardize business logic for Agentic AI enablement