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Databricks

Sr. Manager, Field Engineering - Public Sector

Posted Yesterday
Be an Early Applicant
In-Office or Remote
3 Locations
172K-241K Annually
Senior level
In-Office or Remote
3 Locations
172K-241K Annually
Senior level
The Senior Manager will lead the Solutions Architects team for Federal System Integrators and Defense Industrial Base, focusing on technical sales, hiring, and team development to drive customer success with Databricks' offerings.
The summary above was generated by AI

FEQ127R74

While candidates in other locations are encouraged for this role, we are primarily targeting candidates local to the Washington DC, Maryland, Virginia areas. 

Mission

We are seeking a Senior Manager, Solutions Architects (SAs) to lead our Federal System Integrators and Defense Industrial Base (FSI/DIB) 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 operates efficiently to help accelerate Databricks' market growth.

The Impact You Will Have

  • Alongside the sales Director, you will set the vision and strategy for how this team will accelerate transformative outcomes for the FSIs and DIBs customers
  • You will hire, train, lead and grow the Solutions Architect team for a company in high-growth mode.
  • Help your customers achieve exceptional success with Databricks and deliver substantial 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
  • 5+ years of experience in the data space with a technical product (i.e. data warehousing, big data, machine learning, or more recently with generative AI).
    • Alternatively, 5+ years of experience in mission-focused space impacting DIB or FSI from a technology perspective
  • Trusted advisor to technical executives that guide strategic data infrastructure decisions.
  • Lead a team through best practices for technical qualification, technical validations, architecture discussions, and product demonstrations.
  • Strategic mindset focused on driving customer outcomes in an accelerated fashion
  • Experience hiring candidates that continually raise the bar, ramping them up to be successful, and promoting into larger roles.
  • Create a positive morale for the team and help foster a working relationship between Field Engineering, Sales, and other important internal cross-functional teams.
  • Experience working cross-functionally with other teams such as Sales, Product Management, Engineering, and Customer Success.
  • Technical and business skills to earn the trust of Engineering talent and leadership at Databricks.
  • Demonstrated architectural influence. Able to influence and review complex architectures; guiding your team and customers towards ideal solutions - that scale.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.


Local Pay Range
$171,800$240,500 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. 

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Top Skills

Big Data/Analytics
Data Engineering
Data Science
Data Warehousing
Generative Ai

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