Senior Forward Deployed Engineer – Public Sector

Jobtailor; Virginia (IL); On-site; USD 140,000 - 190,000; Full time

Job summary

Jobtailor is seeking a senior data engineering leader to drive production-grade data systems, architectures, and ML/AI integrations for federal government engagements. You will guide end-to-end design, build, and deployment across AWS/Azure/GCP environments using Spark and Databricks best practices.

You will own architectures, collaborate with cross-functional teams, and ensure secure, scalable solutions while influencing the Databricks product roadmap and accelerators for broader impact.

Qualifications

• 6+ years of experience in data engineering, data platforms and analytics, or software engineering.
• Fluency writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
• Working knowledge of at least two 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, documentation, and whiteboarding.
• Experience working with enterprise clients and managing conflicts across broad stakeholder groups.
• Active Secret or Top Secret clearance required.
• Databricks Certification preferred.

Responsibilities

• Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations.
• Guide strategic federal government 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 projects to support evaluation and adoption of Databricks.
• 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 Engineers and Customer Support to provide product and implementation feedback and resolve engagement-specific issues.
• Embed with customer teams and engage stakeholders from technical individual contributors to executives.
• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Skills

Data Engineering

Python Programming

Apache Spark

MLOps

Databricks Certification

Data Platforms

Analytics

Software Engineering

Cloud Ecosystems

CI/CD

Data Architectures

Data Pipelines

ML/AI Models

JavaScript/TypeScript

Scala

Tools

AWS

Azure

GCP

Databricks

Job description

• Lead customer technical projects by delivering production-grade systems, reference architectures, custom applications, data ingestion, and ML/AI model integrations


• Guide strategic federal government 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 projects to support evaluation and adoption of Databricks


• 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 Engineers and Customer Support to provide product and implementation feedback and resolve engagement-specific issues


• Embed with customer teams and engage stakeholders from technical individual contributors to executives


• Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap

Requirements

• 6+ years of experience in data engineering, data platforms and analytics, or software engineering


• Fluency 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, documentation, and whiteboarding


• Experience working with enterprise clients and managing conflicts across broad stakeholder groups


• Active Secret or Top Secret clearance required


• Databricks Certification preferred

Core Competencies

Demonstrates expertise in leading technical projects for federal government clients, focusing on the design, build, and deployment of scalable data architectures and AI applications. Proficient in Python, Scala, and cloud ecosystems, with a strong emphasis on MLOps and Databricks best practices.

Highest-signal resume keywords

• Data Engineering


• Python Programming


• Apache Spark


• MLOps


• Databricks Certification

ATS Optimization Keywords

Hard Skills

• Data Platforms


• Analytics


• Software Engineering


• Cloud Ecosystems


• CI/CD


• Data Architectures


• Data Pipelines


• ML/AI Models


• JavaScript/TypeScript


• Scala

Soft Skills

• Stakeholder Management


• Conflict Resolution


• Collaboration

Certifications & Qualifications

• Active Secret Clearance


• Top Secret Clearance


• Databricks Certification

Industry Keywords

• Big Data


• AI Applications


• Technical Project Delivery


• Production Deployments


• Reference Architectures

Tools & Technologies

• AWS


• Azure


• GCP


• Databricks