Forward Deployed Engineer, FDE – L4

Databricks

. Work with customers to build and productionize solutions to data and AI challenges using the Databricks platform .

Posted 10/19/2026full-timeRemote • IndiaSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering and AI solutions, with a strong focus on architecture, design, and deployment of scalable systems using the Databricks platform. Proven ability to lead technical projects, collaborate with diverse stakeholders, and deliver production-grade applications that meet customer needs.

Highest-signal resume keywords

Data EngineeringDatabricks PlatformApache SparkPython ProgrammingCloud Ecosystems

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data PlatformsSoftware EngineeringMLOpsCI/CDData ArchitectureMachine Learning ModelsJavaScriptTypeScriptScalaDistributed Computing

Soft Skills

Documentation SkillsConflict ManagementCuriosityAdaptabilityStakeholder Engagement

Tools & Technologies

AWSAzureGCPDatabricksAI APIs

Certifications & Qualifications

Databricks Certification

Industry Keywords

Big DataTechnical Project DeliveryEnd-to-End SystemsProduction DeploymentsCustomer Engagement

Tech Stack

Tools & technologies

ApacheAWSAzureBootstrapCloudGoogle Cloud PlatformJavaScriptPythonScalaSparkTypeScript

About the role

Key responsibilities & impact

Work with customers to build and productionize solutions to data and AI challenges using the Databricks platform
Own architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development
Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integration
Guide strategic customers through end-to-end design, build, and deployment of big data and AI applications
Scope technical delivery work with engagement managers and customer input
Guide customers on architecture and design; bootstrap or implement customer projects
Ensure solutions are secure, scalable, and aligned with customer needs and Databricks best practices
Collaborate with Databricks technical teams, Project Managers, Architects, Customer teams, Engineering, and Customer Support
Provide product and implementation feedback and guide resolution of engagement-specific product and support issues
Embed with customer teams and engage stakeholders from technical individual contributors to executives
Contribute accelerators, frameworks, and best practices that scale across accounts and influence the Databricks product roadmap
Train customers and support their technical implementation needs

Requirements

What you’ll need

9+ years of experience in data engineering, data platforms & analytics, or software engineering
Comfortable writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks
Working knowledge of at least two common 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
Experience designing and deploying performant production end-to-end data architectures and applications combining data pipelines, ML/AI models, and user-facing interfaces
Experience with technical project delivery, including managing scope, timelines, measurable outcomes, and translating complex concepts into actionable solutions
Documentation and white-boarding skills
Experience working with enterprise clients and managing conflicts across a broad stakeholder range
Curiosity, adaptability, and eagerness to explore technologies supporting deployment and integration of Databricks-based solutions
Willingness to travel to customers 20% of the time
Databricks Certification

Benefits

Comp & perks

Comprehensive benefits and perks; specific regional details provided via Databricks benefits document