Forward Deployed Engineering Manager

The shape of it

In the posting’s own words

As a Forward Deployed Engineering (FDE) Manager, you will lead a high-performing delivery team of 8+ Individual Contributors (ICs) to build and productionize solutions for customers' data and AI challenges using the Databricks platform. You are responsible for ensuring high-quality technical execution, driving professional services business outcomes, and nurturing elite engineering talent while remaining close to the technology and execution.

What it asks for · 4

• Experience: 8+ years of total technical experience with 2+ years of experience managing, leading, or mentoring high-caliber technical teams in data engineering, data platforms, software engineering, or AI/ML.
• Technical Depth: Strong technical background capable of evaluating architectures spanning distributed computing (Apache Spark™), Python/Scala, modern cloud ecosystems (AWS, Azure, GCP), CI/CD, and MLOps/GenAI frameworks.
• Leadership Skills: Proven ability to manage technical project delivery, timelines, scoping, conflict resolution, and executive customer relationships from technical ICs up to Director level.
• Certifications: Databricks Certification required (or path to completion).

What the job covers

• Connect your team’s day-to-day work to real customer outcomes and business impact. Build excitement about Databricks by sharing customer wins and delivery successes, making each individual feel motivated and appreciated.
• Reinforce your team’s top delivery priorities. Help your team focus on high-impact technical work, redirecting effort away from low-value tasks and removing blockers that slow execution. Use delivery data and PS KPIs to confirm focus areas.
• Hire strong PS talent using structured interviews and practical delivery scenarios. Ensure team takes 2–4 protected hours a week for continuous technical learning and experimentation. Understand your team’s strengths and growth areas to provide regular coaching, and handle underperformance early with clear feedback and accountability.
• Remove delivery blockers quickly, using simple automation or AI assistants to accelerate routine work. Run consistent inspection rhythms (standups, project reviews, retrospectives) and hold teammates strictly accountable to timelines and quality bars.
• Translate Databricks’ Culture Principles (Customer Obsessed, Truth Seeking, First Principles, Raise the Bar, Company-First, Bias for Action) into concrete day-to-day behaviors, ensuring standards are upheld in all customer interactions.
• Apply a builder and AI-first mindset to improve team productivity. Review delivery plans and architectures utilizing practical knowledge of the Databricks platform and cloud environments (AWS, Azure, GCP). Actively coach ICs on secure, scalable deployment patterns, governance, and production readiness.

Tools and skills named

Words the posting leans on

• delivery11×
• technical10×
• customer6×
• engineering5×
• execution5×
• data4×
• account3×
• cloud3×
• ensuring3×
• experience3×
• ics3×
• impact3×
• platform3×
• architectures2×
• areas2×
• aws azure2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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