Enterprise Data Engineering Lead

Enterprise Data Engineering Lead

Location:

Grand Rapids, MI, 49503

At Perrigo, we are driven by our mission to Makes Lives Better Through Trusted Health and Wellness Solutions, Accessible to All. We are proud to be a Top 10 player in the European Consumer Self‑Care market and the largest U.S. store brand provider of over‑the‑counter and infant formula. Dedicated to providing The Best Self‑Care for Everyone, we are the people behind the brands you trust:
Opill®, Compeed®, Solpadeine®, NiQuitin®, and many more. We Are Perrigo. We are committed to enhancing the wellbeing of our colleagues and consumers alike. We pride ourselves on fostering an inclusive, collaborative culture where each person can experience a sense of belonging.

Join us on our One Perrigo journey as we evolve to win in self‑care.

This is a strategic leadership role within the Data, Analytics & AI organization, focused on building and scaling Perrigo’s enterprise data engineering capabilities. The Data Engineering Lead will be responsible for designing, implementing, and optimizing data pipelines, platforms, and architecture to support analytics, AI/ML, and business intelligence across the company. This role reports directly to the VP - Data, Analytics & AI and will play a critical role in Perrigo’s digital transformation journey.

• Architect E2E data solutions in cloud environments (Azure or AWS), encompassing data ingestion, data lake, data warehouse, real‑time streaming, modeling, and consumption.
• Develop and maintain enterprise data architecture frameworks, standards & principles
• Lead the design and implementation of scalable, secure, and high‑performance data pipelines.
• Define and enforce data engineering standards, best practices, and governance across teams.
• Collaborate with data scientists, analysts, and business stakeholders to ensure data availability and usability.

• Build and maintain robust ETL/ELT pipelines for structured and unstructured data sources.
• Optimize data workflows for performance, reliability, and cost‑efficiency.
• Ensure data quality, lineage, and observability across all pipelines.

• Evaluate and implement modern & emerging tools and cloud platforms (e.g., Azure, Databricks) to improve data engineering capabilities.
• Drive automation and CI/CD practice in data engineering workflows.
• Integrate data platforms with enterprise systems including ERP, CRM, and external data sources.

• Lead and mentor a team of data engineers, fostering a culture of innovation and continuous improvement.
• Partner with IT and business leaders to align data engineering initiatives with strategic goals.
• Promote agile methodologies and cross‑functional collaboration.

• Ensure compliance with data privacy regulations (e.g., GDPR, HIPAA) and internal security policies.
• Implement data governance frameworks in collaboration with data stewards and legal teams.

• Technical Expertise:
  Proficiency in Python, Scala, SQL, Spark, and cloud‑native data platforms. Expertise in SQL/ No
  
  SQL databases (e.g., Postgre
  
  SQL, Mongo
  
  DB, Big Query, or similar).
• Architecture & Design:
  Strong background in designing & building high performance data lakehouse, real‑time streaming, and microservices architecture.
• Project Management:
  Proven ability to lead complex data initiatives and deliver results on time.
• Communication:
  Excellent verbal and written communication skills, with the ability to influence stakeholders.
• Leadership:
  Demonstrated success in building and leading high‑performing data engineering teams.
• Problem Solving:
  Strong analytical mindset with a focus on scalable solutions.
• 10+ years of experience with Cloud platforms and Cloud data warehouses.
• These skills are typically acquired through the completion of a Bachelor’s degree in computer science, engineering, or closely related field; combined with 10‑14 years of experience in data engineering, with at least 3 years in a leadership role.
• Masters degree preferred.

We believe our people are…