Enterprise Data Engineering Lead

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 contributes to Perrigo’s digital transformation.

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 & 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 tools and cloud platforms 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 and internal security policies; implement data governance frameworks 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 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 ability to influence stakeholders.
• Leadership: Demonstrated success in building and leading high-performing data engineering teams.
• Problem Solving: 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 related field, with 10-14 years of data engineering experience; at least 3 years in a leadership role.
• Master's degree preferred.

Skills

• Cloud data engineering
• Data Lakehouse architecture
• ETL/ELT design and optimization
• Data governance and security
• CI/CD for data workflows
• Stakeholder management
• Agile methodologies

Education

• Bachelor's degree in computer science, engineering, or closely related field; Master‚Äôs degree preferred.