Enterprise Data Engineering Lead
Perrigo Company plc
Full-time
Remote friendly (Grand Rapids, MI)
United States
IT
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Role Summary
Enterprise Data Engineering Lead responsible for designing, implementing, and optimizing data pipelines, platforms, and architecture to support analytics, AI/ML, and business intelligence across the company. Reports to the VP - Data, Analytics & AI and plays a critical role in Perrigo’s digital transformation journey.
Responsibilities
- Architect end-to-end data solutions in cloud environments (Azure or AWS), including data ingestion, data lake, data warehouse, real-time streaming, modeling, and consumption.
- Develop and maintain enterprise data architecture frameworks, standards, and 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 and emerging tools and cloud platforms to improve data engineering capabilities.
- Drive automation and CI/CD practices 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 and internal security policies; implement data governance frameworks in collaboration with data stewards and legal teams.
Qualifications
- Technical Expertise: Proficiency in Python, Scala, SQL, Spark, and cloud-native data platforms; expertise in SQL/NoSQL databases (e.g., PostgreSQL, MongoDB, BigQuery).
- Architecture & Design: Strong background in designing and 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.
- Bachelor’s degree in computer science, engineering, or closely related field; 10–14 years of data engineering experience with at least 3 years in a leadership role; Master’s degree preferred.
Skills
- Cloud data architecture and governance
- ETL/ELT design and optimization
- Data quality, lineage, and observability
- Real-time data processing
- Strategic leadership and team development
- Stakeholder management and collaboration
Education
- Bachelor’s degree in computer science, engineering, or closely related field; Master’s degree preferred.