Lead Data Engineer

COMPANY OVERVIEW We exist to make food the world loves. But we do more than that. Our company is a place that prioritizes being a force for good, a place to expand learning, explore new perspectives and reimagine new possibilities, every day. We look for people who want to bring their best — bold thinkers with big hearts who challenge one another and grow together. Because becoming the undisputed leader in food means surrounding ourselves with people who are hungry for what’s next.​ OVERVIEW As a Lead Data Engineer, you will help shape how connected data drives business action across General Mills by designing scalable, sustainable data solutions and advancing modern data engineering practices. You will work closely with data engineers, business analysts, architects, and cross-functional partners to define technical direction, enable strategic initiatives, and bring new data capabilities to life across global teams. This is a strong opportunity to influence data strategy, modernize the data engineering ecosystem, and mentor technical talent in a highly collaborative environment. KEY ACCOUNTABILITIES Act as a data and analytics leader with strong technical and domain expertise to guide 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. Makes 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 performances issues and research root cause analysis in the cloud data ecosystem Actively contributes work to the broader GMI data community and collaborates with others to refine common libraries Mentor and guide data engineers, fostering innovation, technical excellence, and strong engineering practices within the team. Assist in hiring & onboarding MINIMUM QUALIFICATIONS Education: 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. PREFERRED QUALIFICATIONS 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. ELIGIBILITY Applicants must meet minimum age qualifications in the country in which the job is located.