Senior Forward Deployed Engineer (Technical Data Architect)

Databricks
London
Workplace: HybridFull timeFunction: Data Science & Machine LearningSkills: ["Customer empathy","Adaptability","Curiosity","Documentation","Stakeholder management"]

Build and productionize customer-facing data and AI solutions on the Databricks platform. Own end-to-end technical architecture and design decisions, delivering production-grade data engineering, ML/AI integration, and custom applications. Collaborate with engineering, project management, and customer teams to scope delivery, guide adoption, and resolve implementation issues. Contribute reusable accelerators and best practices that scale impact across accounts while traveling to customers as needed.

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FursaFursa
Databricks
Databricks
1 week ago

Senior Forward Deployed Engineer (Technical Data Architect)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Build and productionize customer-facing data and AI solutions on the Databricks platform. Own end-to-end technical architecture and design decisions, delivering production-grade data engineering, ML/AI integration, and custom applications. Collaborate with engineering, project management, and customer teams to scope delivery, guide adoption, and resolve implementation issues. Contribute reusable accelerators and best practices that scale impact across accounts while traveling to customers as needed.
Location: London
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Lead production solution delivery for customer projects, including reference architectures, custom applications, and data ingestion/ML-AI model integration.
  • •Guide strategic customers through end-to-end design, build, and deployment of big data and AI applications.
  • •Bootstrap and implement customer projects to improve understanding, evaluation, and adoption of Databricks.
  • •Own architecture and design decisions to ensure solutions are secure, scalable, and aligned to Databricks best practices.
  • •Work cross-functionally with engineering, project managers, and customer teams; provide product and implementation feedback and help resolve engagement issues.
Travel: Medium travel

Key Requirements

  • •Experience in data engineering, data platforms & analytics, or software engineering/full stack development.
  • •Comfort writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks.
  • •Working knowledge of two or more cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
  • •Deep experience with distributed computing using Apache Spark, including Spark runtime internals.
  • •Working knowledge of CI/CD, MLOps, ML/AI models, and AI APIs; experience designing and deploying end-to-end data architectures and applications.
Skills:Customer empathyAdaptabilityCuriosityDocumentationStakeholder management
Certifications:Databricks Certification
Languages:English
Tech Stack:PythonScalaJavaScriptTypeScriptApache SparkAWSAzureGCPCI/CDMLOpsML/AIAI APIsDistributed computing

Company Brief

Databricks
Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series E+
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn