Senior Engineering Manager, Data Engineering
About The Position
At Crisis Text Line, our data platform powers the technology, research, and insights behind our crisis services—and it’s evolving quickly as our products, global reach, and AI/ML capabilities grow. In this role, you’ll lead a lean Data Engineering team with broad ownership across our production data ecosystem. You’ll shape the evolution of our Databricks and AWS platform, tackle complex challenges across reliability, governance, data quality, and multi-tenant architecture, and build the infrastructure that enables what comes next in AI/ML. You’ll pair deep technical leadership with strong people leadership—developing engineers, setting technical direction, and creating an environment where a versatile team can do its best work while continuing to grow its capabilities and impact.
Requirements
- 10+ years in data engineering, infrastructure, or ML platforms; 5+ years in people leadership.
- Proven experience building Databricks + AWS ecosystems.
- Proficiency in Python, SQL, and Terraform with strong AI Engineering principles.
- Track record improving observability, automation, and data reliability.
- Experience with data governance and compliance (HIPAA/SOC 2).
- Excellent communication and stakeholder partnership across technical and non-technical teams.
- Reliable High-Speed Internet Required: Must have a stable high-speed internet connection to support seamless remote collaboration, virtual meetings, online job tasks, etc.
Nice To Haves
- Built or scaled an AI Engineering function or major data modernization program.
- Managed global or multi-region data environments.
- Experience balancing innovation with operational stability and control.
- Mix of enterprise discipline and startup agility.
Responsibilities
- Oversee the evolution of our Databricks-based lakehouse and ML platform, defining the technical roadmap for data pipelines and AI/ML infrastructure.
- Drive infrastructure-as-code practices with Terraform and make key architectural decisions that enable scalable, reliable global data systems.
- Ensure reliability, performance, and cost efficiency across Databricks and AWS by implementing observability, monitoring, and SLA frameworks for critical data pipelines.
- Establish best practices for DataOps, AI Engineering, and data quality while balancing innovation with technical debt and tracking KPIs for platform health, productivity, and business impact.
- Partner with Product, Analytics, Data Science, and Research teams to deliver scalable, compliant data solutions.
- Collaborate with Developer Platform, Security, and Compliance teams to align shared infrastructure, governance, and business priorities.
- Build, mentor, and scale a high-performing data and ML engineering team focused on innovation and reliability.
- Foster a culture of technical excellence, collaboration, and continuous learning across the organization.
Benefits
- Comprehensive medical, dental, and vision options that prioritize accessibility and financial peace of mind
- Employer-funded HSA contributions
- Generous PTO, sick time, and 19 paid holidays with a winter break
- 12 weeks of fully paid parental leave after 26 consecutive weeks of service
- Monthly internet and mental health stipends
- Annual Wellness Stipend
- Home office and professional development stipends
- 403(b) retirement plan with employer contribution
- Sabbatical after 3 years of service
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
