Lead Data Engineer - Azure/Databricks Data Platform

Nestle SA; St. Louis (MO); On-site; USD 138,000 - 188,000; Full time

Benefits offered by this job

401k match

Healthcare coverage

Benefits package

Job summary

Nestle9 is seeking a Lead Data Engineer to act as the technical lead for a data product team focused on a specific data domain. You will build, test, deploy, and maintain production-grade data pipelines and ensure integration into the enterprise data model.

You will collaborate with data engineers, product owners, and stakeholders to mature the data platform and develop long-term roadmaps, emphasizing Azure, Databricks, and Python/PySpark.

Qualifications

• Bachelors degree from an accredited college or university.
• 7+ years of professional data engineering experience.
• 4+ years of experience in Azure ecosystem.
• 4+ years of experience with Databricks and Python/PySpark.

Responsibilities

• Serve as the technical lead for a data product team focused on a specific data domain.
• Develop, test, deploy, and maintain data pipelines to move, transform, and harmonize source data into data products ready for consumption by end users, applications, and other data product teams.
• Ensure adherence to Purinas data engineering and architectural standards.
• Monitor performance of data pipelines developed and owned within the assigned data domain.
• Champion the adoption of best practices within the data engineering guild.
• Coach and mentor other data engineers.
• Collaborate with other engineers and architects to mature the data enterprise data platform.
• Collaborate with product owners and business stakeholders to develop long-term data product roadmaps.
• Collaborate with stakeholders and data product team to define data product requirements.

Education

Bachelors degree

Tools

Azure

Databricks

Python/PySpark

Job description

Nestle9 is seeking a Lead Data Engineer to act as the technical lead for a data product team focused on a specific data domain. You will build, test, deploy, and maintain production-grade data pipelines and ensure integration into the enterprise data model.

You will collaborate with data engineers, product owners, and stakeholders to mature the data platform and develop long-term roadmaps, emphasizing Azure, Databricks, and Python/PySpark.