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Sr. Data Engineer

Job in Denver, Denver County, Colorado, 80285, USA
Listing for: Socket.dev
Full Time position
Listed on 2026-09-21
Job specializations:
  • IT/Tech
    Data Engineering
Salary/Wage Range or Industry Benchmark: 180000 - 200000 USD Yearly USD 180000.00 200000.00 YEAR
Job Description & How to Apply Below

About Sonder Mind

At Sonder Mind, we believe everyone deserves one personalized, connected, and effective mental health destination to take care of their mental health and well-being at any stage of life. Sonder Mind care encompasses everything from therapy and medication management to meditation and mindfulness exercises. Our clinicians leverage our digital tools and research to deliver increasingly high-quality care and to develop thriving practices.

Combining technology and human connection, Sonder Mind drives better outcomes through our comprehensive approach. Learn more about Sonder Mind at  or download the mobile app, available on iOS and Android.

To follow the latest Sonder Mind news, get to know our clients, and learn about what it’s like to work at Sonder Mind, you can follow us on Instagram, Linkedin, and Twitter.

Additionally, we expect all team members to effectively leverage modern AI technologies as part of their everyday workflow, and to continuously adapt as new tools emerge. Familiarity with job-relevant AI platforms such as Gemini, ChatGPT, Claude, Git Hub Copilot or other industry-standard AI productivity tools is expected and considered essential for success at this company.

About the Role

We are hiring a Senior Staff Data Engineer to play a senior technical leadership role on Sonder Mind’s Data Platform team. This role focuses on designing, building, and evolving the data systems that support analytics, experimentation, machine learning, and clinical outcomes across the business.

As a Senior Staff Data Engineer you will operate with a high degree of ownership and autonomy. You will be responsible not only for delivering reliable data infrastructure, but also for shaping technical direction, establishing best practices, and enabling other teams to move faster with high-quality, trusted data; while operating within the constraints of a regulated healthcare environment.

What you’ll do
  • 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.

What does success look like?

First 3–6 Months:

  • Develop a strong understanding of Sonder Mind’s data landscape, key business use cases, and regulatory constraints.

  • Take ownership of critical pipelines or platform components and begin making meaningful improvements to reliability and clarity.

  • Build trust with analytics, data science, and engineering partners through consistent delivery and thoughtful technical decisions.

Continued Success in the Role

  • Data pipelines are reliable, observable, and well understood, with fewer surprises and…

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