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.