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Nestle

Lead Data Engineer

Nestle

. Serve as the technical lead for a data product team focused on a specific data domain .

Posted 10/30/2026full-timeSt. Louis • Missouri • United StatesSenior💰 $137,759 - $188,424 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data engineering, focusing on developing and maintaining data pipelines within the Azure ecosystem, while adhering to architectural standards and best practices. Proven ability to collaborate with stakeholders and mentor team members in a data product environment.

Highest-signal resume keywords
Data EngineeringAzure EcosystemDatabricksPython/PySparkData Pipeline Development

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data Pipeline DevelopmentData TransformationData HarmonizationPerformance MonitoringData Product Requirements Definition
Soft Skills
CoachingMentoringCollaboration
Tools & Technologies
AzureDatabricksPythonPySpark
Industry Keywords
Data Engineering StandardsData Product RoadmapsEnterprise Data PlatformData Engineering Guild

Tech Stack

Tools & technologies
AzurePySparkPython

About the role

Key responsibilities & impact
  • Serve as the technical lead for a data product team focused on a specific data domain
  • Develop, test, deploy, and maintain data pipelines
  • Move, transform, and harmonize source data into data products
  • Ensure adherence to Purina’s data engineering and architectural standards
  • Monitor performance of data pipelines within the assigned data domain
  • Champion best practices within the data engineering guild
  • Coach and mentor other data engineers
  • Collaborate with engineers and architects to mature the enterprise data platform
  • Collaborate with product owners and business stakeholders on long-term data product roadmaps
  • Define data product requirements with stakeholders and the data product team

Requirements

What you’ll need
  • Bachelor’s degree from an accredited college or university
  • 7+ years of professional experience, including 5+ years of practical, hands-on data engineering
  • 4+ years of experience in the Azure ecosystem
  • 4+ years of experience with Databricks and Python/PySpark
  • Must not require visa sponsorship

Benefits

Comp & perks
  • Performance-based incentives
  • 401k with company match
  • Healthcare coverage
  • Competitive total rewards package
  • Inclusive work environment
  • Reasonable accommodations during recruitment