Sr. Forward Deployed Engineer - Apache Spark NEW

The Briefed; Austin (TX); On-site; USD 182,000 - 250,000; Full time

Job summary

The Briefed is seeking a Senior Forward Deployed Engineer (Sr. FDE) in the Central or Eastern Time Zone to partner with enterprise clients, designing and productionizing end-to-end data and AI solutions.

You will own architectures, build distributed data pipelines with Apache Spark, integrate ML/AI models, and create user-facing interfaces as a billable technical lead embedding with client teams. You will drive architecture decisions across data engineering, MLOps, and full-stack development,

Qualifications

• 6+ years of experience in data engineering, data platform architecture, software development, or analytics engineering.
• Proficient in Python, Scala, or JavaScript/TypeScript with modern frameworks.
• Hands-on Apache Spark experience with performance optimization.
• Experience with AWS, Azure, and/or GCP, with deep expertise in at least one.
• Familiarity with MLOps pipelines, ML frameworks, AI APIs, and end-to-end data architectures with user interfaces.
• CI/CD experience for production deployments.
• Databricks Certification (Data Engineer, ML or Platform).
• Strong consulting and customer-delivery track record.

Responsibilities

• Lead high-impact technical engagements for enterprise clients by architecting and delivering production-grade data pipelines, reference architectures, custom applications, and ML/AI model integrations.
• Lead design and architectural decisions across data engineering, MLOps, and full-stack development—ensuring systems built on Databricks are secure, performant, scalable, and aligned with industry best practices.
• Embed with customer engineering pods and executive stakeholders to deeply understand technical challenges, bootstrap transformational projects, and drive long-term platform adoption.
• Partner with Engagement Managers, Solution Architects, Core Engineering, and Customer Support to meet milestones and rapidly resolve engagement issues.
• Contribute reusable frameworks, technical accelerators, and best practices that scale impact across global accounts while providing field feedback to product teams.
• Manage technical scope, delivery timelines, and measurable outcomes while whiteboarding architectures and resolving complex stakeholder trade-offs.

Skills

Python

Scala

JavaScript/TypeScript

Apache Spark

AWS

Azure

GCP

MLOps

CI/CD

Databricks Certification

Tools

Databricks

Job description

As a Senior Forward Deployed Engineer (Sr. FDE) based in the Central or Eastern Time Zone, you will work directly with strategic enterprise customers to design, build, and productionize end-to-end solutions for their most complex data and AI challenges. Combining advanced software engineering, distributed computing, and consultative delivery expertise, you will own application architectures, implement distributed data pipelines with Apache Spark™, integrate ML/AI models and APIs, and build user-facing application interfaces. Senior FDEs operate as billable technical leads, embedding deeply with client engineering and executive teams to turn complex requirements into production-grade systems while building reusable accelerators that shape the core Databricks product roadmap.

Key Responsibilities

• Production Solution Delivery: Lead high-impact technical engagements for enterprise clients by architecting and delivering production-grade data pipelines, reference architectures, custom applications, and ML/AI model integrations.
• End-to-End Architecture Ownership: Lead design and architectural decisions across data engineering, MLOps, and full-stack development—ensuring systems built on Databricks are secure, performant, scalable, and aligned with industry best practices.
• Customer Immersion & Strategic Advisory: Embed with customer engineering pods and executive stakeholders to deeply understand technical challenges, bootstrap transformational projects, and drive long-term platform adoption.
• Cross-Functional Collaboration: Partner closely with Engagement Managers, Solution Architects, Core Engineering, and Customer Support to ensure technical milestones are met and engagement issues are rapidly resolved.
• Reusable Assets & Scale: Contribute reusable frameworks, technical accelerators, and best practices that scale impact across global accounts while providing field feedback directly to Databricks product teams.
• Technical Project Leadership: Manage technical scope, delivery timelines, and measurable outcomes while 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 Mastery: Strong proficiency writing production-grade code in Python, Scala, or JavaScript/TypeScript along with modern application development frameworks.
• Apache Spark & Distributed Computing: Deep hands-on experience with distributed computing via Apache Spark™, including advanced knowledge of Spark runtime internals and performance optimization.
• Multi-Cloud Ecosystems: Working knowledge of two or more public cloud environments (AWS, Azure, GCP) with deep expertise in at least one.
• AI/ML & Full-Stack Integration: Practical familiarity with MLOps pipelines, machine learning frameworks, AI APIs, and building end-to-end data architectures with user-facing interfaces.
• DevOps & CI/CD: Hands-on experience implementing CI/CD pipelines for production deployments.
• Certifications: Databricks Certification (Data Engineer, ML, or Platform).
• Consulting & Customer Delivery: Demonstrated experience managing scope, whiteboarding architectures, resolving stakeholder conflicts, and delivering complex client engagements.

Preferred Qualifications

• Prior experience working in forward-deployed engineering, technical consulting, or enterprise cloud platform professional services.
• Deep familiarity with lakehouse architectures, Delta Lake, Unity Catalog, and streaming data engines.
• Proven track record of publishing open-source data utilities, technical whitepapers, or reusable platform 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 across Zones 1–4) + 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.