Lead Data Engineer

Overview

Lead Data Engineer role at General Mills to design scalable data solutions, define technical direction, and mentor data engineers across global teams.

What you'll do

• Act as a data and analytics leader, guiding engineering decisions and delivery outcomes.
• Lead project team members to deliver data capabilities.
• Partner with business analysts and architects to define technical architectures for strategic projects and initiatives.
• Evaluate, implement, and deploy emerging data engineering technologies, processes, and practices.
• Make pipeline architecture decisions based on standardized patterns and technologies.
• Lead the design and implementation of scalable data pipelines, data modelling, and data quality frameworks.
• Independently troubleshoot technical and performance issues and research root cause analysis in the cloud data ecosystem.
• Actively contribute work to the broader GMI data community and collaborate with others to refine common libraries.
• Mentor and guide data engineers, fostering innovation, technical excellence, and strong engineering practices.
• Assist in hiring and onboarding.

What you'll need

• Bachelor's degree or equivalent practical experience in a relevant field.
• 12+ years of experience in data engineering, data architecture, or related technology roles.
• Strong experience with modern cloud platforms, preferably Google Cloud.
• Hands-on experience in ETL processes, data warehousing, data quality, data observability, and structured and unstructured data systems.
• Ability to work directly with business partners to design solutions and explain architecture trade-offs clearly.
• Strong technical skills in SQL, Python, BigQuery, Composer, Dataflow, and dbt.
• Experience in Data Modelling, Data Observability, Orchestration, and Prompt Engineering.
• Familiarity with software engineering tools and delivery practices such as Git, GitHub Actions, Jira or Azure DevOps, and Agile ways of working.
• Strong problem-solving and analytical skills with attention to detail.
• Effective verbal and written communication skills, including the ability to explain technical concepts to non-technical stakeholders.
• Collaborative, adaptable, self-driven, and able to take ownership from project initiation through completion.

Nice to have

• Strong hands-on coding skills in Python and SQL.
• Experience developing procedures and scripts for data loading, transformation, and migration.
• Familiarity with Kafka and distributed computing tools.
• Broader experience with cloud technologies, with Google Cloud preferred.
• Strong awareness of AI and its application in data engineering.