Data Engineering Lead – Azure Lakehouse & Pipelines

Watkins Wellness

Livonia (MI)

On-site

USD 103,700 - 163,020

Full time

14 days+
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Job summary

Masco is seeking a Data Engineering Leader to drive the enterprise data engineering capability. The role leads a team of Data Engineers building ingestion, transformation, and Lakehouse solutions powering enterprise analytics.

The candidate will code alongside the team, enforce data validation, and partner with architects on platform decisions. The position requires strong Azure data stack experience, senior engineering leadership, and a track record of delivering reliable data pipelines with

Qualifications

  • Bachelor''s or Master''s degree in CS/Engineering/Data Analytics or related field; equivalent professional experience considered.
  • Proven experience leading data engineering teams with delivery accountability.
  • Extensive hands-on experience building scalable data platforms on Azure.
  • Experience running incident management and SLA-driven support for data pipelines.
  • Experience coordinating onshore and offshore engineering delivery.

Responsibilities

  • Lead, coach, and manage a team of Data Engineers with performance guidance and prioritization.
  • Own ingestion pipelines across retailer, HQ, and BU data sources on Databricks and Azure stack.
  • Contribute as a senior engineer on critical pipelines and Lakehouse design.
  • Oversee incident management, release management, and operation health of pipelines.
  • Monitor cloud costs and contribute to budgeting for data services and tooling.

Skills

Leadership
Delivery focus
Collaboration
Communication
Problem solving

Education

Bachelor''s or Master''s degree in CS/Engineering/Data Analytics

Tools

Databricks
Azure data stack
Databricks Unity Catalog
PowerBI
MLflow
Azure ML

Job description

Masco is seeking a Data Engineering Leader to drive the enterprise data engineering capability. The role leads a team of Data Engineers building ingestion, transformation, and Lakehouse solutions powering enterprise analytics.

The candidate will code alongside the team, enforce data validation, and partner with architects on platform decisions. The position requires strong Azure data stack experience, senior engineering leadership, and a track record of delivering reliable data pipelines with

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