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Job Description - Principal, Data Engineering at CargillAbout the Company
Cargill is a global leader in agriculture, food production, and commodity trading, dedicated to nourishing the world in a safe, responsible, and sustainable manner. With a rich history spanning over 150 years, Cargill operates in over 70 countries, providing innovative solutions across the food, agriculture, financial, and industrial sectors. The company is committed to creating value for its customers, stakeholders, and communities by leveraging cutting-edge technologies and sustainable practices. Cargill’s core values emphasize integrity, respect, and a relentless pursuit of excellence, making it a trusted partner in the global marketplace.
About The Role
The Principal, Data Engineering at Cargill is a strategic leadership position responsible for driving the design, development, and maintenance of sophisticated data systems that support business insights and decision-making processes. This role requires a seasoned expert who can lead technical teams, influence architectural standards, and develop innovative data solutions using the latest cloud-based and big data technologies. The ideal candidate will possess a deep understanding of data pipelines, infrastructure, and modeling, ensuring data is accessible, reliable, and optimized for analytics and reporting. As a key member of the data leadership team, this role involves collaborating with cross-functional stakeholders to align data strategies with organizational objectives and foster a culture of data-driven decision making.
Qualifications
The ideal candidate will have a minimum of 6 years of relevant experience in data engineering or related fields, with many professionals bringing over 10 years of expertise. A strong educational background in computer science, information technology, or related disciplines is preferred. Candidates should demonstrate expertise in cloud data platforms, data ingestion, streaming, transformation, and DevOps practices. Proven experience leading architectural initiatives, establishing best practices, and managing large-scale data environments is essential. Familiarity with technologies such as Snowflake, AWS, Kafka, Spark, and open lakehouse ecosystems is highly desirable. The ability to evaluate and implement scalable, maintainable, and innovative data solutions is critical for success in this role.
Preferred qualifications include defining long-term technical strategies, championing operational excellence, and making strategic decisions that balance speed, cost, risk, and flexibility. Deep expertise in cloud data warehouses, data lakes, and open table formats, along with hands-on experience with data ingestion tools like AWS Glue and Kafka, are highly valued. Strong skills in data streaming architectures, data transformation using Spark, and DevOps practices such as CI/CD are also important. The candidate should demonstrate leadership qualities, a proactive mindset, and the ability to work collaboratively across teams to drive data innovation and excellence.
Responsibilities
- Provide thought leadership on the design and development of data pipelines that facilitate the seamless movement of data from various sources to internal databases, ensuring data integrity and accessibility.
- Influence the construction and optimization of data infrastructure, ensuring data formats are suitable for analysis and support organizational needs.
- Identify and implement improvements in data formats to enhance usability and accessibility across the organization.
- Build and maintain strong relationships with stakeholders to understand their data requirements and align data initiatives with business objectives.
- Lead the development and deployment of scalable, sustainable, and robust data products and solutions utilizing advanced engineering and cloud-based technologies.
- Drive the development of standards and prototypes for new data frameworks and architecture patterns that support efficient processing and analysis.
- Develop automated reporting systems that deliver timely insights, enabling data-driven decision making across the organization.
- Provide leadership in data modeling, ensuring data is well-prepared and structured for analytics, reporting, and pipeline development.
- Oversee the implementation of data ingestion and streaming architectures, ensuring high performance and reliability.
- Champion DevOps practices within the data engineering team, including code management, continuous integration, and deployment strategies.
Benefits
Cargill offers a comprehensive benefits package designed to support the health, well-being, and professional growth of its employees. This includes competitive salary packages, health insurance, retirement plans, and paid time off. Employees have access to continuous learning opportunities, leadership development programs, and a collaborative work environment that fosters innovation. The company also emphasizes work-life balance and offers flexible working arrangements where applicable. Cargill’s commitment to sustainability and community engagement provides employees with meaningful opportunities to contribute positively to society while advancing their careers.
Equal Opportunity
Cargill is an equal opportunity employer committed to creating an inclusive environment for all employees. We celebrate diversity and are dedicated to providing equal employment opportunities regardless of race, gender, age, religion, disability, sexual orientation, or any other protected characteristic. We believe that diverse teams drive innovation and success, and we actively promote a culture of respect, fairness, and opportunity for everyone.
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