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Databricks

Builds cloud software for data analysis and AI

Senior Forward Deployed Engineer - Multiple Teams

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeSeattle, WA, 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 MLOps, machine-learning and artificial-intelligence models, and AI application programming interfaces.
  • Experience designing and deploying performant, production-grade 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.
  • Curiosity, adaptability, and eagerness to learn 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.
  • Databricks certification.

Responsibilities

  • Lead customer technical projects by delivering production-grade systems, designing and building reference architectures and custom applications, and integrating data ingestion with machine-learning and artificial-intelligence models.
  • Guide strategic customers through transformational big data projects, including end-to-end design, build, and deployment of big data and AI applications; work with engagement managers to scope technical delivery with customer input.
  • Guide customers on architecture and design, and bootstrap or implement customer projects to support successful 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 Databricks technical staff, project managers, architects, and customer teams to deliver engagement technical components in line with customer needs.
  • Work with Engineering and Databricks 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 ranging 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.
  • Work with customers to build and productionize solutions to data and AI challenges using the Databricks platform, implementing end-to-end systems across data engineering, AI, 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 maximize the value of their data.
  • Complete billable customer projects according to specification.

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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