CSQ127R318
As a Sr. Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data.
This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.
The impact you will have:
- Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration
- Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
- Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
- Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
- Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
- Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
- Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
- Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.
What we look for:
- 6+ years experience in data engineering, data platforms & analytics, or software engineering
- Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
- Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
- Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
- Familiarity with CI/CD for production deployments
- Working knowledge of MLOps, ML/AI models and AI APIs
- Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces.
- Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions.
- Documentation and white-boarding skills.
- Experience working with enterprise clients and managing conflicts across a broad stakeholder range
- Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects.
- Travel to customers 20% of the time
- Databricks Certification
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 base 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 anticipated 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.
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 click here.
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.
Skills Required
- 6+ years experience in data engineering, data platforms & analytics, or software engineering.
- Proficient coding in Python, Scala, JavaScript/TypeScript and modern frameworks.
- Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
- Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
- Familiarity with CI/CD for production deployments.
- Working knowledge of MLOps, ML/AI models and AI APIs.
- Design and deployment of performant production end-to-end data architectures combining data pipelines, ML/AI models, and user interfaces.
- Experience with technical project delivery: managing scope, timelines and measurable outcomes.
- Documentation and white-boarding skills.
- Experience working with enterprise clients and managing cross-stakeholder conflicts.
- Willingness to travel to customers approximately 20% of the time.
- Databricks Certification.
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
-
Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
-
Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
-
Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
.png)
