Sr. Forward Deployed Engineer (FDE)

About the role

This position focuses on working directly with manufacturing clients to build and deploy production-grade data and AI systems using the Databricks platform. You will serve as a technical lead, managing the full lifecycle of complex projects while collaborating with internal product and engineering teams to shape future roadmaps. In this capacity, you will act as a critical bridge between customer needs and Databricks' evolving product capabilities. The role requires a balance of hands-on technical implementation and strategic advisory functions. You will be responsible for translating complex business requirements into robust technical solutions. Success in this position depends on your ability to deliver measurable outcomes while maintaining a high degree of ownership. You will influence not only individual client projects but also contribute to the broader product strategy. This is a role designed for an experienced engineer who thrives in ambiguous, client-facing environments.

Key facts

What you'll do

• Architect and implement end-to-end data pipelines, AI models, and custom applications for enterprise clients using Databricks.
• Lead technical project delivery by managing scope, timelines, and measurable outcomes to ensure alignment with client objectives.
• Create reusable assets, frameworks, and best practices to improve deployment efficiency and consistency across multiple accounts.
• Act as a technical advisor to stakeholders, ranging from individual contributors to executive leadership, to guide strategic technology decisions.
• Provide actionable feedback to internal engineering and support teams to resolve product issues and influence the product roadmap based on real-world usage.
• Assist customers in evaluating and adopting the Databricks platform by bootstrapping initial implementations and providing architectural guidance.
• Design and implement performant, secure, and scalable data architectures that meet the specific needs of manufacturing environments.
• Troubleshoot complex production issues and optimize existing deployments to improve reliability, performance, and cost-efficiency.
• Collaborate with sales and pre-sales teams to define technical proof-of-concepts and validate solution hypotheses for prospective clients.
• Document technical designs, implementation details, and operational procedures to ensure clarity and continuity across engagements.
• Mentor junior engineers and data specialists within client environments to promote best practices and platform adoption.
• Evaluate emerging technologies and techniques to identify opportunities for innovation within client data and AI initiatives.

Requirements

• 6+ years of professional experience in software engineering, data platforms, or data engineering, with a strong track record of delivery.
• Proficiency in Python, Scala, or JavaScript/TypeScript, demonstrating the ability to write clean, maintainable code.
• Deep expertise in distributed computing, specifically with Apache Spark and its runtime internals, including performance tuning.
• Practical experience with MLOps, AI APIs, and AI/ML models, including training, deployment, and monitoring workflows.
• Familiarity with CI/CD workflows for production environments, including infrastructure as code and automated testing strategies.
• Experience designing and deploying performant, end-to-end data architectures that integrate with existing enterprise systems.
• Ability to manage enterprise-level stakeholder relationships and resolve conflicts through clear communication and technical insight.
• Strong documentation and white-boarding capabilities to articulate technical concepts to diverse audiences.
• Databricks Certification or equivalent demonstrable expertise on the Databricks platform.
• U.S. eligibility to obtain a security clearance may be required for certain client engagements.
• Willingness to comply with Databricks compliance requirements, including potential U.S. government licensing for export-controlled technology.

Nice to have

• Working knowledge of at least two cloud ecosystems, such as AWS, Azure, or GCP, and their core services.
• Experience with manufacturing data landscapes, including IoT, time-series data, or supply chain analytics.
• Familiarity with regulatory frameworks relevant to manufacturing, such as data privacy or industry-specific standards.
• Demonstrated success in leading multi-phase engagements from initial scoping through production deployment.
• Knowledge of data governance, lineage, and quality frameworks within a distributed computing context.

Practical notes

• Salary range: $182,000 - $250,208 USD.
• Total compensation may include equity, annual performance bonuses, and benefits.
• Travel expectation is 20%, requiring periodic travel to client sites within the assigned region.
• Compliance: Databricks may require a U.S. government license for roles involving export-controlled technology or source code, and may decline applicants based on this requirement.
• This role is full-time and based in Philadelphia, Pennsylvania, with the expectation of consistent availability for client needs.