# Senior Forward Deployed Engineer - Public Sector

**Company:** [Databricks](https://hotfix.jobs/companies/databricks)
**Location:** Remote
**Role:** Solutions Architecture
**Salary:** $182k – $250k/yr
**Experience:** 6+ years
**Skills:** Python, Scala, JavaScript, TypeScript, AWS, Azure, GCP, Spark, CI/CD, MLOps, Machine Learning, Ai Apis, Data Engineering, Data Architecture, Databricks
**Posted:** 2026-08-14

> This customer-facing engineer leads architecture, development, and production deployment of Databricks-based data and AI solutions for enterprise and public-sector clients. The role requires 6+ years of engineering experience, cloud and Apache Spark expertise, and the ability to manage technical delivery across diverse stakeholders.

## Job Description

## Responsibilities

- Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
- Guide strategic customers through the design, build, and deployment of big data and AI applications.
- Scope technical delivery work with engagement managers and customers.
- Advise customers on architecture and design, and bootstrap or implement projects that support successful evaluation and adoption of the Databricks platform.
- Own architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
- Collaborate with Databricks technical teams, project managers, architects, and customer teams to deliver technical engagement components.
- Work with Engineering and Customer Support to provide product and implementation feedback and resolve engagement-specific issues.
- Embed with customer teams and engage stakeholders ranging from technical individual contributors to executives.
- Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the product roadmap.

## Requirements

- 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
- Ability to write code in Python, Scala, JavaScript, or TypeScript, and use modern frameworks.
- Working knowledge of at least two cloud ecosystems among AWS, Azure, and Google Cloud, 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, machine learning and AI models, and AI APIs.
- Experience designing and deploying performant, production-grade end-to-end data architectures and applications combining data pipelines, ML/AI models, and user-facing interfaces.
- Experience delivering technical projects, including managing scope and timelines, measuring outcomes, and translating complex concepts into actionable solutions.
- Documentation and whiteboarding skills.
- Experience working with enterprise clients and managing conflicts across broad stakeholder groups.
- Curiosity, adaptability, and eagerness to explore technologies that support deployment and integration of Databricks-based solutions.
- Ability to travel to customers 20% of the time.
- Databricks Certification.

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