Senior Data Engineer

Headspace

8d•$122,400 - $195,500•Hybrid

About The Position

As a Senior Data Engineer at Headspace, you will help build the modern data platform that powers personalized, ethical, and scalable mental health support for millions of members. In this role, you will design and implement robust data pipelines, partner closely with analytics, data science, and engineering teams, and help create a secure, compliant, and privacy-focused data foundation. This is an opportunity to do high-impact work at the intersection of data, innovation, and mission—enabling smarter decisions, better member experiences, and the future of personalized mental health care.

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

Nice To Haves

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

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