Forward Deployed Engineer - Apache Spark & AI NEW

The Briefed; United States; Remote; USD 182,000 - 250,000; Full time

Benefits offered by this job

Compensation & equity

Healthcare coverage

401(k) plan

Flexible PTO

Job summary

Databricks is seeking a Forward Deployed Engineer (FDE) to work directly with strategic enterprise customers, architect and productionize data and AI solutions, and drive platform adoption. You will lead evangelizing architectures, deliver production-grade pipelines, and build user-facing interfaces leveraging Apache Spark and multi-cloud ecosystems.

You will deeply integrate with client teams, own technical scope, and contribute towards reusable accelerators and product feedback, enabling

Qualifications

• 6+ years of professional experience in data engineering, data platform architecture, software development, or analytics engineering.
• Proficient in Python, Scala, or JavaScript/TypeScript with modern frameworks.
• Deep experience with Apache Spark and distributed systems; strong performance tuning.

Responsibilities

• Lead production-grade data pipelines and reference architectures for enterprise customers.
• Own end-to-end architecture across data engineering, ML, and full-stack components.
• Embed with customer teams to bootstrap projects and drive platform adoption.
• Collaborate with engagement managers, architects, and support to meet milestones and resolve issues.
• Contribute reusable accelerators and provide feedback to product teams.

Skills

Python

Scala

JavaScript/TypeScript

Apache Spark

Distributed systems

Multi-cloud

MLOps

CI/CD

Databricks Certification

Consulting & Customer Delivery

Tools

Delta Lake

Unity Catalog

Job description

Databricks is the Data and AI company. Over 20,000 organizations worldwide—including 70% of the Fortune 100—rely on the Databricks Data + AI Platform to build and scale data and AI applications, analytics, and autonomous agents.

As a Forward Deployed Engineer (FDE), you will work directly with strategic enterprise customers to design, build, and productionize end-to-end solutions for their most challenging data and AI problems. Combining software engineering, distributed computing, and customer-facing delivery skills, you will own application architectures, implement big data pipelines with Apache Spark™, integrate ML/AI models and APIs, and build user-facing interfaces. FDEs operate as billable technical leads, embedding deeply with client teams to turn complex requirements into production-grade systems while creating reusable accelerators that shape the core Databricks product roadmap.

Key Responsibilities

• Production Solution Delivery: Lead high-impact customer engineering engagements by architecting and delivering production-grade data pipelines, reference architectures, custom web applications, and ML/AI model integrations.
• End-to-End Architecture Ownership: Lead design decisions across data engineering, MLOps, and full-stack development—ensuring systems built on Databricks are secure, scalable, and maintainable.
• Customer Immersion & Advisory: Embed with customer engineering pods and technical executives to deeply understand business goals, bootstrap projects, and drive long-term platform adoption.
• Cross-Functional Collaboration: Partner with Engagement Managers, Solution Architects, Core Engineering, and Customer Support to ensure technical milestones are met and engagement issues are rapidly resolved.
• Reusable Assets & Platform Feedback: Contribute reusable frameworks, technical accelerators, and best practices to scale impact across accounts while providing field feedback to Databricks product teams.
• Technical Scope & Project Management: Manage technical scope, timelines, and measurable delivery outcomes, whiteboarding architectures and resolving complex stakeholder trade-offs.

Requirements

Software & Data Engineering Technical Depth

• 6+ years of professional experience in data engineering, data platform architecture, software development, or analytics engineering.
• Polyglot Coding Skills: Strong proficiency writing production code in Python, Scala, or JavaScript/TypeScript along with modern development frameworks.
• Apache Spark & Distributed Systems: Deep hands-on experience with distributed computing via Apache Spark™, including an understanding of Spark runtime internals and performance tuning.
• Multi-Cloud Expertise: Working knowledge of two or more public cloud ecosystems (AWS, Azure, GCP) with deep expertise in at least one environment.
• AI/ML & Application Integration: Practical familiarity with MLOps frameworks, machine learning models, modern AI APIs, and building end-to-end data platforms with user-facing interfaces.
• CI/CD & DevOps: Hands-on experience implementing CI/CD deployment pipelines for production software and data workloads.
• Certifications: Databricks Certification (Data Engineer, ML, or Platform).
• Consulting & Customer Delivery: Proven track record in technical project delivery, whiteboarding, and managing cross-functional enterprise stakeholders.

Preferred Qualifications

• Experience working in forward-deployed, professional services, or technical consulting roles within cloud data platform ecosystems.
• Hands-on experience with modern lakehouse architectures, Delta Lake, Unity Catalog, and streaming data engines.
• Track record of authoring open-source data utilities, technical blogs, or reusable solution accelerators.

Selection & Interview Process

1. Recruiter Screen
2. Hiring Manager Screen
3. Design and Architecture Interview
4. Live Coding Assessment
5. Technical Presentation
6. Reference Check

Total Rewards & Benefits

• Compensation & Equity: Pay range of $182,000 – $250,208 USD (On-Target Earnings) + annual performance bonus eligibility + Databricks equity grants.
• Healthcare & Wellbeing: Comprehensive medical, dental, and vision insurance coverage for employees and eligible dependents.
• Financial & Retirement: 401(k) plan options, life/disability coverage, and employee wellness stipends.
• Time Off & Flexibility: Flexible PTO, paid company holidays, paid sick leave, and parental leave.