Senior Forward Deployed Engineer (Technical Data Architect)

Overview

In this role, you will architect and deliver production-grade data, AI, and application solutions for customers using the Databricks platform. You’ll lead design decisions, own end-to-end architectures, and collaborate with cross-functional teams to scale impact across accounts. You’ll work hands-on with data engineering, ML/AI, and software delivery while ensuring secure, scalable implementations. Expect close customer engagement, preprocessing to deployment, and the creation of reusable accelerators to drive adoption and value.

Pay / Benefits

• comprehensive benefits and perks

Responsibilities

• Lead production-grade solution delivery, including reference architectures, data ingestion, and ML/AI model integration
• Guide strategic customers through end-to-end design, build, and deployment of big data and AI applications
• Own architecture and design decisions for secure, scalable solutions aligned with customer needs and Databricks best practices
• Collaborate with cross-functional teams (engineering, PM, customer success) to ensure delivery meets objectives
• Embed with customer teams to understand challenges and deliver measurable impact
• Develop accelerators, frameworks, and best practices to scale impact across accounts
• Provide product and implementation feedback to leverage rapid resolution of engagement issues
• Support customer education and empowerment to adopt Databricks solutions
• Contribute to knowledge sharing and artifacts that can be reused across engagements
• Travel to customers ~20%

Key requirements

• Experience in data engineering, data platforms & analytics, or software engineering/full stack development
• Proficiency in Python, Scala, JavaScript/TypeScript, and modern frameworks
• Experience with two or more cloud ecosystems (AWS, Azure, GCP) and expertise in at least one
• Deep experience with distributed computing using Apache Spark and knowledge of Spark internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps, ML/AI models, and AI APIs
• Design and deployment of end-to-end data architectures combining pipelines, ML/AI models, and UIs
• Experience with technical project delivery, scoping, timelines, and measurable outcomes
• Documentation and white-boarding skills
• Experience with enterprise clients and stakeholder management
• Willingness to travel to customers (20%)
• Databricks Certification is an advantage
• Customer empathy
• Adaptability
• Curiosity
• Databricks Platform
• Apache Spark
• Python/Scala/JavaScript/TypeScript

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