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Databricks

Builds cloud software for data analysis and AI

Senior Forward Deployed Engineer - Forward Deployed Engineer, Healthcare & Life Sciences

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeAtlanta, GA, USA

About the Job

Requirements

  • At least 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 common cloud ecosystems (AWS, Azure, or Google Cloud Platform), with expertise in at least one.
  • Deep experience with distributed computing using Apache Spark and knowledge of Spark runtime internals.
  • Familiarity with continuous integration and continuous delivery for production deployments.
  • Working knowledge of machine learning operations, machine learning and artificial intelligence models, and artificial intelligence application programming interfaces.
  • Experience designing and deploying performant, production, end-to-end data architectures and applications combining data pipelines, machine learning and artificial intelligence models, and user-facing interfaces.
  • Experience delivering technical projects, including managing scope, timelines, and measurable outcomes and translating complex concepts into actionable solutions.
  • Documentation and whiteboarding skills.
  • Experience working with enterprise clients and managing conflicts across a broad range of stakeholders.
  • Ability to build skills in technical areas and explore technologies that support deployment and integration of Databricks-based solutions for customer projects.
  • Willingness to travel to customers 20% of the time.

Responsibilities

  • Deliver impactful customer technical projects by building production-grade systems, reference architectures, custom applications, data ingestion, and machine learning and artificial intelligence model integrations.
  • Guide strategic customers implementing transformational big data projects, including end-to-end design, build, and deployment of big data and artificial intelligence applications; work with engagement managers and customers to scope technical delivery work.
  • 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 and ensure solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
  • Coordinate with the Databricks technical team, project manager, architect, and customer team to deliver technical engagement components that meet customer needs.
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback and help resolve engagement-specific product and support issues.
  • Embed with customer teams and engage technical individual contributors and executives to understand challenges and deliver impact.
  • Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.
  • Work with customers to build and productionize solutions to data and artificial intelligence challenges using the Databricks platform; own architecture, lead design decisions, and implement end-to-end systems spanning data engineering, artificial intelligence, and application development.
  • Work cross-functionally with engineering, product, and developer relations to shape long-term strategic priorities and initiatives.
  • Integrate with client systems and provide training and other technical support to help customers get value from their data.
  • Complete billable customer projects according to specification with customer empathy.

Desired Qualifications

  • Databricks Certification
  • Curiosity, adaptability, and eagerness to explore new technologies supporting deployment and integration of Databricks-based solutions.

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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