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Sr. Manager, Field Engineering - Financial Services; Banking

Job in Washington, Tazewell County, Illinois, 61571, USA
Listing for: Cacheflow
Full Time position
Listed on 2026-09-22
Job specializations:
  • Management
  • IT/Tech
Salary/Wage Range or Industry Benchmark: 192100 - 264175 USD Yearly USD 192100.00 264175.00 YEAR
Job Description & How to Apply Below

FEQ
327R251

Candidates in the listed region are encouraged for this role, we are open to remote candidates with a preference in the North East or Midwest at one of our office hubs.

Mission

Reporting to a Director, Field Engineering, the Sr. Manager, Field Engineering will help lead a team of Solutions Architects (SAs) for the Financial Services segment of Databricks’ Regulated Industries Field Engineering team. You will lead and promote a diverse 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 achieve success through Databricks’ Data Intelligence Platform.

You will 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 of highly qualified, bar‑raising candidates
  • You will establish relationships across the business to make your customers and team successful
  • You will keep your team of SAs ahead of the technical curve by ensuring they maintain advanced knowledge of the Databricks technology stack
  • You will ensure 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‑sales teams - hiring, on‑boarding, coaching and mentoring those teams to mature and grow into highly capable individual operators as well as exceptional team‑players
  • 10+ 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)
  • 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
  • Establish and foster external partnerships with systems integrators (SIs) and independent software vendors (ISVs) that maximize and accelerate client success
  • Strong understanding of consumption‑driven business models and the recipes for long term growth and success
  • Experience hiring candidates that continually raise the bar, ramping them up to be successful, and promoting into larger roles
  • Create a positive culture and morale for the team - fostering strong working relationships 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
  • Must be technical enough to earn the trust of Engineering talent and leadership at Databricks
  • Ability 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…

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