Tonal is looking to shape the backbone of their data platform by designing and scaling systems that bring together massive volumes of workout, sensor, and health-related data while ensuring security, reliability, and trust. This role requires a deep understanding of compliance and security standards and the ability to build infrastructure that protects sensitive information while fueling product innovation, AI, and analytics.
Requirements
- Strong skills in SQL, Python, and distributed data processing (Spark, Databricks, or similar).
- Experience building pipelines with DBT, Airflow, F Fivetran, or related tools.
- Background in data modeling and warehousing with systems like Snowflake, Databricks, or Redshift.
- Hands-on experience working with regulated environments and sensitive data.
- Familiarity with frameworks such as HIPAA, SOC 2, and NIST for security and compliance.
- Skilled in access control design, audit logging, encryption, and governance.
- Experience with fitness, healthcare, IoT, or sensor data.
Responsibilities
- Architect secure and scalable data systems that support Tonal’s growth and meet regulatory standards.
- Build and optimize data models and pipelines across diverse sources: sensors, workouts, health integrations, CRM, payments, and content.
- Establish controls for access, encryption, anonymization, monitoring, and auditability.
- Define and enforce best practices for managing sensitive data, including PHI and PII.
- Conduct risk assessments and implement safeguards guided by NIST frameworks.
- Support SOC 2 audits by documenting and demonstrating effective security controls.
- Continuously evolve the platform, introducing new tools and frameworks to balance innovation with strong regulatory posture.
Other
- 8+ years of experience in data engineering, or 6+ years with a Master’s degree (or equivalent).
- Collaborate with teams across Product, Engineering, Sports Science, and Healthcare to translate needs into compliant solutions.
- Mentor engineers and scientists, setting high standards for secure data engineering.
- Excellent communicator who can explain complex tradeoffs to both technical and non-technical audiences.
- Known for technical leadership and mentoring, raising the bar for engineering quality.
