Senior Data Engineer / Senior Data Engineeress

About Cargill

Cargill is dedicated to delivering food and agricultural solutions that nourish the world safely, responsibly, and sustainably. At the heart of the supply chain, we collaborate with farmers and customers to source, create, and deliver essential products for living.

With a team of 155,000 members, we innovate with purpose, providing vital resources so businesses can grow, communities can thrive, and consumers can live well. With over 160 years of experience as a family-owned company, we are focused on the future while staying true to our core values: putting people first, reaching higher, and doing the right thing for today and future generations.

Job Purpose and Impact

The Senior Data Engineer - Digital Technology & Data, Agriculture & Trading is responsible for designing, building, and maintaining complex data products that enable effective data analysis and reporting. This role requires a focus on efficiently processing large data sets to support trading decision-making.

The ideal candidate will have expertise in Oracle PL SQL for managing existing application back-ends and will possess strong skills in SQL and Python, along with experience using the Snowflake platform. Familiarity with KAFKA, DBT, Airflow, and Astronomer will be advantageous for future projects. Previous experience with trading-related data is also beneficial.

Key Accountabilities

• Data Infrastructure: Prepares data infrastructure for efficient data storage and retrieval.
• Data Formats: Examines and resolves appropriate data formats to enhance data usability and accessibility across the organization.
• Data & Analytical Solutions: Develops complex data products using advanced engineering and cloud-based technologies, ensuring scalability and sustainability.
• Data Pipelines: Creates and maintains streaming and batch data pipelines for seamless data ingestion and transformation.
• Data Systems: Reviews existing data systems to identify improvement and optimization opportunities.
• Stakeholder Management: Collaborates with multi-functional data and analytic teams to gather requirements and ensure functional and non-functional needs are met.
• Data Frameworks: Builds complex prototypes to test new concepts and implements data engineering frameworks that enhance data processing capabilities.
• Automated Deployment Pipelines: Develops automated pipelines to improve code deployment efficiency with suitable governance.
• Data Modeling: Performs complex data modeling aligned with datastore technology for sustainable performance and accessibility.

Qualifications

Minimum requirement of 5 years of relevant work experience.

Our Offer

We provide a stimulating international environment that will challenge your abilities and harness your talents. Alongside a competitive salary and benefits package, we offer outstanding career development opportunities within one of the largest and most stable private companies globally.

Application Process

Apply online using the form below. Only applications matching the job profile will be considered.