Sr. Manager, Field Engineering - Public Sector (SLED)
Databricks - United States
Posted Apr 21, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Sr. Manager, Field Engineering - Public Sector (SLED) United States FEQ427R164 Mission Reporting to a Director of Field Engineering, the Sr. Manager will help lead a team of SAs for the SLED segment of Databricks' Public Sector Field Engineering team. You will lead and promote a dynamic team focusing on enterprise software, big data/analytics, data engineering, data science, data warehousing and generative AI. Leading the technical sales team, you will partner with Sales (and other Field Engineering technical segments) to increase revenue and help customers become wildly successful. You'll scale and maintain an outstanding Field Engineering team that is efficient in its operations to help accelerate Databricks' growth in the market. The Impact You Will Have - You will hire, train, and grow a team of Solutions Architects for a company in high-growth mode. - Make your customers extremely successful with Databricks and provide outsized value to their businesses. - You will maintain a robust hiring pipeline at all times. - Establish relationships across the business to make your customers and team successful. - Keep your team of SAs ahead of the technical curve. An SA adds value by maintaining advanced knowledge of the technology stack. You will make sure that your team is continuously learning and working to provide our customers with the most comprehensive solutions for their needs What We Look For - Proven experience building and leading technical pre(or post)-sales teams - hiring, on-boarding, and enabling pre(or post)-sales professionals - 8+ years of experience in the data
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