Databricks

1 day ago

Sr. Forward Deployed Engineer (FDE) - Retail

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Work with retail customers to design and productionize data and AI solutions on the Databricks platform. Own architecture and lead end-to-end delivery spanning data engineering, ML/AI model integration, and application development, collaborating with engineering, product, project management, and developer relations. Guide customers through transformational big-data and AI initiatives, embed with stakeholder teams, and contribute reusable accelerators that scale impact across accounts and influence the product roadmap.

Location: Denver, California

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead production-grade customer technical projects, including reference architectures, custom applications, and data ingestion with ML/AI integration.
•Guide transformational customer big data and AI initiatives from end-to-end design through build and deployment, scoping work with engagement managers.
•Assist customers with architecture and design and bootstrap/implement projects to drive evaluation, adoption, and successful understanding of Databricks.
•Own architecture and design decisions to ensure solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
•Collaborate with Databricks engineering, project teams, and customer support to deliver technical engagement components and provide product/implementation feedback, including rapid resolution of engagement-specific issues.

Travel: Medium travel

Pay and Benefits

Salary: USD 182,000 - 250,208 annually

Key Requirements

•6+ years of experience in data engineering, data platforms/analytics, or software engineering.
•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 knowledge of Spark runtime internals.
•Experience with CI/CD, MLOps, ML/AI models, and AI APIs, plus production deployment of end-to-end data architectures.
•Documentation and white-boarding skills, along with experience delivering technical projects with measurable outcomes.

Experience:6+ yearsData engineeringData platformsAnalyticsBig dataMLOpsEnterprise clientsDistributed computing

Skills:Customer empathyAdaptabilityCuriosityStakeholder communicationDocumentation

Certifications:Databricks Certification

Languages:English

Tech Stack:PythonScalaJavaScriptTypeScriptApache SparkAWSAzureGCPCI/CDMLOpsML/AI modelsAI APIsMLflowDelta Lake

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

Website LinkedIn

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Databricks

1 day ago

Sr. Forward Deployed Engineer (FDE) - Retail

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Denver, California

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Lead production-grade customer technical projects, including reference architectures, custom applications, and data ingestion with ML/AI integration.
•Guide transformational customer big data and AI initiatives from end-to-end design through build and deployment, scoping work with engagement managers.
•Assist customers with architecture and design and bootstrap/implement projects to drive evaluation, adoption, and successful understanding of Databricks.
•Own architecture and design decisions to ensure solutions are secure, scalable, and aligned with customer needs and Databricks best practices.
•Collaborate with Databricks engineering, project teams, and customer support to deliver technical engagement components and provide product/implementation feedback, including rapid resolution of engagement-specific issues.

Travel: Medium travel

Pay and Benefits

Salary: USD 182,000 - 250,208 annually

Key Requirements

•6+ years of experience in data engineering, data platforms/analytics, or software engineering.
•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 knowledge of Spark runtime internals.
•Experience with CI/CD, MLOps, ML/AI models, and AI APIs, plus production deployment of end-to-end data architectures.
•Documentation and white-boarding skills, along with experience delivering technical projects with measurable outcomes.

Experience:6+ yearsData engineeringData platformsAnalyticsBig dataMLOpsEnterprise clientsDistributed computing

Skills:Customer empathyAdaptabilityCuriosityStakeholder communicationDocumentation

Certifications:Databricks Certification

Languages:English

Tech Stack:PythonScalaJavaScriptTypeScriptApache SparkAWSAzureGCPCI/CDMLOpsML/AI modelsAI APIsMLflowDelta Lake

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

Website LinkedIn