Lead Data Engineer

Job description

**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.