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Jobgether logo
Jobgether

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Lead Data Engineer

Location

United States

Posted

133 days ago

Salary

0

Seniority

Lead

Job Description

Lead Data Engineer

Jobgether

Role Description This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Data Engineer - REMOTE. You will play a crucial role in shaping the backbone of the data platform, ensuring security, reliability, and trust while managing vast volumes of data from workouts and health-related sources. Your expertise will directly impact product innovation, AI, and analytics, allowing our partner to continue redefining the training experience. By building and scaling data systems, you'll contribute to personalizing experiences and enhancing coaching. Your work will ensure that sensitive information is protected while maintaining compliance with an ever-evolving regulatory landscape. - Architect secure and scalable data systems that support growth and meet regulatory standards. - Build and optimize data models and pipelines across diverse sources: sensors, workouts, and health integrations. - Establish controls for access, encryption, anonymization, monitoring, and auditability. - Define and enforce best practices for managing sensitive data, including PHI and PII. - Collaborate with teams across various departments to translate needs into compliant solutions. - Conduct risk assessments and implement safeguards guided by NIST frameworks. - Support SOC 2 audits by documenting and demonstrating effective security controls. - Mentor engineers and scientists, setting high standards for secure data engineering. - Continuously evolve the platform, introducing tools and frameworks to balance innovation with regulatory compliance. Qualifications - 8+ years of experience in data engineering, or 6+ years with a Master’s degree (or equivalent). - Strong skills in SQL, Python, and distributed data processing (Spark, Databricks, or similar). - Experience building pipelines with DBT, Airflow, 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. - 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. Benefits - Flexible work schedule with remote opportunities. - Collaborative work environment with cross-functional teams. - Opportunities for professional growth and development. - Inclusive culture that celebrates diversity and nurtures unique perspectives. - Support for accessible work arrangements and accommodations. - Innovative projects that leverage cutting-edge technology and data. - Participation in ongoing training and skill enhancement programs.

Job Requirements

  • 8+ years of experience in data engineering, or 6+ years with a Master’s degree (or equivalent).
  • Strong skills in SQL, Python, and distributed data processing (Spark, Databricks, or similar).
  • Experience building pipelines with DBT, Airflow, 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.
  • 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.

Benefits

  • Flexible work schedule with remote opportunities.
  • Collaborative work environment with cross-functional teams.
  • Opportunities for professional growth and development.
  • Inclusive culture that celebrates diversity and nurtures unique perspectives.
  • Support for accessible work arrangements and accommodations.
  • Innovative projects that leverage cutting-edge technology and data.
  • Participation in ongoing training and skill enhancement programs.

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