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Databricks

Builds cloud software for data analysis and AI

Senior Forward Deployed Engineer - Public Sector

AI Application EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of experience in data engineering, data platforms and analytics, or software engineering.
  • Fluency in 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, machine learning and artificial intelligence models, and AI APIs.
  • Experience designing and deploying performant, production end-to-end data architectures and applications that combine data pipelines, machine learning and artificial intelligence models, and user-facing interfaces.
  • Experience with technical project delivery, documentation, and whiteboarding.
  • Experience working with enterprise clients and managing conflicts across a broad range of stakeholders.

Responsibilities

  • Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications, data ingestion, and machine learning and artificial intelligence model integration.
  • Guide strategic customers as they implement transformational big data projects, including end-to-end design, build, and deployment of big data and artificial intelligence applications; scope technical delivery work with engagement managers and customer input.
  • Guide customers on architecture and design, and bootstrap or implement customer projects to support their understanding, evaluation, and adoption of Databricks.
  • Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
  • Work with the Databricks technical team, project managers, architects, and customer teams to deliver technical components that meet customer needs.
  • Work with engineers and customer support to provide product and implementation feedback and guide rapid resolution of engagement-specific product and support issues.
  • Embed with customer teams and engage stakeholders from technical individual contributors to executives to understand challenges and deliver impact.
  • Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

Desired Qualifications

  • At least 8 years of experience in data engineering, data platforms and analytics, or software engineering.
  • Databricks certification.
  • Expertise in MLOps, machine learning and artificial intelligence models, and AI APIs.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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