Staff Data Engineer- Data Architect

About the Staff Data Engineer at Headspace

At Headspace, our mission is to transform mental healthcare to improve the health and happiness of the world. We’re looking for an experienced Data Architect who can also operate hands-on as a Staff Data Engineer. You will design and evolve our domain-based Enterprise Data Model (EDM), lead Master Data Management (MDM) initiatives, and build production-grade data pipelines in Python / PySpark. The ideal candidate is comfortable whiteboarding conceptual models, building and reviewing ETL jobs, and coaching engineering teams on data architecture best practices.

Location : This is a hybrid role located in our San Francisco office, working 3 days per week from the office.

What you will do

Lead the Development of Scalable Data Infrastructure :

Drive the architecture and implementation of pySpark data pipelines to ingest and transform diverse datasets into the data lake in a fault-tolerant, robust system.

Set Design Patterns :

Drive the creation and enforcement of standard conventions in code, architecture, schema design, and table design.

Architect World-Class Data Platforms :

Design and lead the evolution of secure, compliant, and privacy-forward data warehousing platforms for healthcare.

Strategic Collaboration for Business Insights :

Partner with analytics, product, and engineering leaders to ensure the data ecosystem provides actionable and reliable insights into critical business metrics.

Champion Data-Driven Leadership :

Mentor other members of the DE and broader data team, particularly around dbt architecture and query performance, and foster a data-first culture across teams.

Influence Organizational Strategy :

Act as a technical thought leader, shaping the company’s data strategy and influencing cross-functional roadmaps with data-centric solutions.

What you will bring

7+ years in data engineering / architecture, with 2+ years leading EDM / MDM programs and a track record of leading initiatives at scale.

Experience creating and maintaining domain-based enterprise data models (canonical, hub-and-spoke, data-product-oriented).

Deep expertise with data-modeling tools (ERwin, ER / Studio, PowerDesigner, or equivalent) and modeling techniques (3NF, Dimensional, Data Vault, Anchor).

Production experience writing performant Python and PySpark code on distributed compute (Spark 3+, Delta Lake).

Strong SQL skills across columnar and relational engines (Snowflake, Redshift, Databricks SQL, Postgres).

Solid grasp of data-governance practices : lineage, glossaries, PII / PHI controls, and data-quality frameworks.

Ability to articulate architecture choices to both executive stakeholders and hands-on engineers.

Experience designing and optimizing real-time and batch ETL pipelines (dbt preferred), with scalability and reliability.

Systems thinker who balances near-term delivery with long-term architecture vision.

Comfortable in collaborative, agile environments; able to mentor cross-functional teams.

Excellent written and verbal communication; able to translate complex data topics into plain language.

Bias for automation, documentation, and continuous improvement.

Nice-To-Haves

Hands-on with Databricks platform (Unity Catalog, Delta Live Tables, MLflow).

dbt Core for transformation, tests, and metadata; dbt Semantic Layer experience is a plus.

Exposure to event streaming (Kafka, EventHub) and CDC tools.

Experience integrating with commercial MDM suites or building custom match-merge solutions.

Familiarity with cloud data-platform services on AWS (Terraform).

Background in data-privacy standards (GDPR, CCPA, HIPAA) and differential-privacy or tokenization techniques.

The anticipated new hire base salary range for this full-time position is

$140,400-$224,250

• equity + benefits.

Our salary ranges are based on the job, level, and location, and reflect the lowest to highest geographic markets where we are hiring for this role within the United States. Within this range, individual compensation is determined by a candidate’s location as well as a range of factors including but not limited to : unique relevant experience, job-related skills, and education or training. Your recruiter will provide more details on the specific salary range for your location during the hiring process.

At Headspace, base salary is one component of our Total Rewards package. We offer a robust package including base salary, stock awards, comprehensive healthcare, wellness stipend, retirement match, and more. Details about Total Rewards will be provided during the recruitment process.

About Headspace

Headspace exists to provide every person access to lifelong mental health support. We combine evidence-based content, clinical care, and innovative technology to help millions of members around the world get support that’s effective, personalized, and accessible whenever and wherever they need it.

We live our values daily : Make the Mission Matter, Iterate to Great, Own the Outcome, and Connect with Courage. These values shape our decisions, guide our collaborations, and define our culture.

Why You’ll Love Working Here

A mission that matters—with impact you can see and feel

A collaborative, inclusive culture grounded in our values

The chance to shape what mental health care looks like next

Competitive pay and benefits to support your whole self

Diversity, Equity, Inclusion and Belonging

Headspace is committed to a diverse and inclusive environment where everyone can thrive. We do not discriminate on the basis of protected status and are committed to equal opportunity employment. We follow EEOC guidelines and are dedicated to fostering diversity across our workplace.

As an equal opportunity employer, we prohibit discrimination against applicants on the basis of race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, family status, disability, age, veteran status, or any other status protected by law. We may request voluntary self-identification for DEIB reporting; participation is optional and kept confidential.

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