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Salary: USD 180,000 - 200,000 / annual
SonderMind is a digital mental health platform offering therapy, medication management, meditation, and mindfulness exercises. They're seeking a Senior Staff Data Engineer to lead the design, building, and evolution of their data platform that supports analytics, experimentation, machine learning, and clinical outcomes across the business.
In this role, you will operate with high ownership and autonomy, responsible for delivering reliable data infrastructure while shaping technical direction and establishing best practices. You'll design and maintain core data pipelines powering analytics, ML, and AI use cases across product, clinical, and operations teams. Key responsibilities include owning data architecture decisions across ingestion, transformation, storage, and serving layers with focus on scalability, reliability, cost efficiency, and maintainability. You'll establish and enforce data quality, observability, and reliability standards including SLAs, monitoring, alerting, and incident response for critical datasets.
You'll partner closely with analytics, data science, and product engineering teams to understand data needs and translate them into well-designed, reusable data models and pipelines. You'll lead technical initiatives and drive best practices across the data engineering team, including code quality, testing, documentation, and data contracts. A critical aspect of this role is ensuring data systems meet privacy, security, and compliance requirements with strong understanding of handling sensitive mental health and healthcare data. You'll mentor and support other data engineers, providing technical guidance and design feedback to raise the overall engineering bar.
Success in the first 3–6 months means developing strong understanding of SonderMind's data landscape, key business use cases, and regulatory constraints; taking ownership of critical pipelines or platform components; and building trust with analytics, data science, and engineering partners. Continued success involves making data pipelines reliable and observable, enabling teams across the company to move faster with accessible and trusted data, ensuring technical decisions scale well over time, and influencing platform direction by raising standards.
Performance is measured on reliability and quality of core data systems (uptime, freshness, accuracy), impact on team velocity and downstream consumers, technical leadership and influence across the data organization, and alignment with SonderMind's career competencies including ownership, collaboration, and thoughtful problem-solving.
The company emphasizes that all team members should effectively leverage modern AI technologies as part of everyday workflow, with familiarity with job-relevant AI platforms such as Gemini, ChatGPT, Claude, GitHub Copilot, or other industry-standard AI productivity tools expected and considered essential for success.
REQUIREMENTS:
- 8+ years of experience in data engineering, platform engineering, or backend engineering roles
- Strong proficiency in SQL and at least one general-purpose programming language (Python strongly preferred)
- Hands-on experience building and maintaining production data pipelines at scale
- Experience working with modern data platforms, including cloud data warehouses, orchestration tools, and transformation frameworks
- Strong understanding of data modeling, pipeline reliability, and system design trade-offs
- Proven ability to work cross-functionally and translate business needs into effective technical solutions
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
PREFERRED:
- Experience in healthcare, mental health, or other regulated environments
- Familiarity with streaming or event-driven data systems
- Experience supporting machine learning or experimentation workflows
- Exposure to data governance, privacy, or compliance frameworks
