Engineering Manager, Data AI & Analytics

In every role, McCainers are ambitious, curious, and passionate about creating exceptional work experiences – together. With a customer-first mindset, we make doing business with McCain easy.

About the role.

Reporting to the Director of Platform Engineering, Data AI & Analytics, the Data Engineer Manager leads and develops a team of Data Engineers while remaining hands-on in the delivery of scalable, high-quality data solutions. This role plays a critical part in McCain’s global digital transformation by enabling reliable, performant, and trusted data across Agriculture, Manufacturing, and Commercial domains. The Data Engineer Manager partners closely with data architects, analytics teams, and business stakeholders to support enterprise-wide, data-driven decision-making.

What you’ll be doing.

• Lead Data Engineering teams in the design, development, and implementation of scalable data pipelines and data objects across McCain systems


• Provide hands-on technical leadership, coaching, and day-to-day guidance to Data Engineers


• Own end-to-end data ingestion and delivery, including pipeline design, development, maintenance, and supporting infrastructure


• Ensure efficient ELT processes to extract, load, and transform data into the Enterprise Data Platform


• Partner with Data Architects to define and maintain optimized data models, schemas, and database designs


• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into actionable data solutions


• Establish and maintain documentation standards to support Data-as-a-Service and scalable knowledge sharing


• Lead and participate in code reviews, mentoring junior engineers and promoting engineering best practices


• Drive automation, CI/CD, and DevOps practices to improve reliability, scalability, and deployment efficiency


• Continuously evaluate emerging data engineering technologies and incorporate improvements into existing platforms

What you’ll need to be successful.

• Bachelor’s degree or higher in Computer Science, Engineering, or a related field


• Proven experience as a Data Engineer delivering end-to-end data solutions


• Proficiency in one or more languages such as Python, SQL, Java, Scala, Spark, or PySpark


• Experience with modern data platforms such as Databricks, Azure Synapse, Redshift, or similar


• Strong knowledge of data modeling, database design, and data warehousing concepts


• Hands-on experience with cloud platforms such as Azure, AWS, or Google Cloud


• Experience leading or managing agile software development teams


• Strong analytical and problem-solving skills, with the ability to work independently and collaboratively


• Excellent communication skills, with the ability to explain complex technical concepts to non-technical audiences


• Preferred: advanced degree, cloud certifications, DevOps and CI/CD experience, exposure to machine learning or AI technologies, and significant experience leading technical teams

About the team.

You will lead a team of Data Engineers within McCain’s Global Data, AI & Analytics organization. The team partners closely with Platform Engineering, Data Architecture, Analytics, and Digital Product teams to deliver enterprise-grade data capabilities that support McCain’s global business and digital transformation agenda.

About McCain.

Click Here to learn more about McCain and how we provide opportunities to make an impact that matters.

Leadership principles.

• Understanding customer needs


• Driving innovation


• Empowering people


• Taking ownership to deliver results

The McCain experience.

At McCain, you’ll be part of a collaborative, global team that values curiosity, continuous learning, and shared success. We foster an inclusive environment where diverse perspectives are encouraged, leadership is developed at all levels, and individuals are empowered to grow their careers while helping shape the future of food. Our flexible, hybrid work approach supports both personal wellbeing and high performance.