Role overview
Employment type: Full-time
Pay: $128,000 - $176,000/year
Work model: Remote
About the role
The Senior Data Engineer builds and scales data infrastructure supporting mental health products, analytics, research, and clinical outcome measurement. This role combines hands-on development with ownership of cross-functional projects and mentorship, working with clinicians, data scientists, analysts, and product managers.
What you will do
- Build and scale core data infrastructure, pipelines, and services that support products and business decisions.
- Design and implement a robust data warehouse for analytical and operational use cases.
- Develop and maintain efficient data pipelines and curated datasets.
- Work with stakeholders to gather requirements and translate them into technical solutions.
- Write production-ready code daily and take ownership of scalable data projects.
- Lead cross-functional initiatives and provide guidance and mentorship to teammates.
Required qualifications
- 4+ years of experience as a Data Engineer.
- Proven experience writing high-quality, production-ready Python and delivering scalable data projects.
- Expertise in SQL-based data modeling and transformation frameworks such as dbt, including schema management, performance, and data governance.
- Strong experience configuring and deploying ingestion tools, data integration platforms such as Airbyte, commercial ELT pipelines such as Fivetran, and Change Data Capture.
- Hands-on experience building fault-tolerant Apache Airflow pipelines with custom alerting, advanced logging, and automated retries.
- Experience with visualization and analytics tools such as Sigma or Tableau.
- Strong knowledge of Snowflake architecture, including Snowpipe ingestion and open table formats such as Apache Iceberg.
- Strong knowledge of Snowflake administration, security compliance, role-based access control, external authentication, and downstream data consumption.
- Experience with end-to-end data quality assurance, regression testing, and data validation.
- Ability to investigate data discrepancies and tune the performance of complex pipelines.
Preferred qualifications
- Strong foundational knowledge of relational databases, data warehousing principles, and dimensional modeling.
- Experience handling sensitive information, including PII or PHI, in healthcare or similarly regulated environments.
- Experience implementing data masking or redaction processes.
- Familiarity with DevOps principles and infrastructure automation using Terraform.
- Ability to balance engineering quality with tight deadlines.
- Strong communication and consensus-building skills, including translating complex technical problems into actionable business priorities.
Benefits and rewards
- Medical, dental, vision, life, and disability insurance, with FSA/HSA options.
- Coaching and therapy services.
- Company equity through discretionary restricted stock units.
- Paid vacation, sick days, and company holidays.
- Paid parental leave.
- 401(k) with up to 3% employer matching.
- Monthly technology allowance.
- Well-being perks, activities, company merchandise, and community celebrations.
- Potential eligibility for discretionary bonuses.