SonderMind is a company focused on providing personalized mental health care through technology and human connection. They are seeking a Senior Staff Data Engineer to lead the design and development of data systems that support analytics and machine learning, ensuring data quality and compliance within a regulated healthcare environment.
Responsibilities:
- Design, build, and maintain core data pipelines and infrastructure that power analytics, experimentation, machine learning and AI fine tuning and agentic use cases across product, clinical, and operations teams
- Own data architecture decisions related to ingestion, transformation, storage, and serving layers, with a focus on scalability, reliability, cost efficiency, and maintainability
- Establish and enforce data quality, observability, and reliability standards, including SLAs, monitoring, alerting, and incident response practices for critical datasets
- 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
- Lead technical initiatives and drive best practices across the data engineering team, including code quality, testing, documentation, and data contracts
- Ensure data systems meet privacy, security, and compliance requirements, with a strong understanding of handling sensitive mental health and healthcare data
- Mentor and support other data engineers, providing technical guidance, design feedback, and helping raise the overall engineering bar
- Support other responsibilities and ad-hoc projects as needed based on evolving business and platform needs
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
- 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