Sr. Data Engineer

Cargill is a family company committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. We partner with producers and customers to source, make, and deliver products that are vital for living, enabling businesses to grow, communities to prosper, and consumers to live well. This position is within our Food Enterprise, serving food manufacturers, food service customers, and retailers with innovative ingredients and branded products, including poultry, beef, egg, alternative protein, salt, oils, starches, sweeteners, cocoa, and chocolate.

About the role

The Senior Professional, Data Engineering role designs, builds, and maintains complex data systems that enable data analysis and reporting. This position ensures large sets of data are efficiently processed and made accessible for decision-making. Within Food Data Engineering Americas, this role builds and operates data products on Cargill’s Minerva platform, supporting migration off CDP and enabling scalable, governed data solutions for Supply Chain, Procurement & Manufacturing, Commercial Excellence, and LATAM domains.

Responsibilities

• Prepare data infrastructure to support efficient storage and retrieval of data.
• Examine and resolve appropriate data formats to improve data usability and accessibility.
• Develop complex data products and solutions using advanced engineering and cloud-based technologies, ensuring scalability, sustainability, and robustness.
• Develop and maintain streaming and batch data pipelines for seamless data ingestion, transformation, and movement to data stores such as data lakes and warehouses.
• Review existing data systems and architectures to identify areas for improvement and optimization.
• Collaborate with multi-functional data and advanced analytics teams to gather requirements and ensure data solutions meet functional and non-functional needs.
• Build complex prototypes to test new concepts and implement data engineering frameworks that improve data processing capabilities.
• Develop automated deployment pipelines to improve the efficiency of code deployments with fit-for-purpose governance.
• Perform complex data modeling in accordance with datastore technology to ensure sustainable performance and accessibility.
• Build and maintain data products within the Minerva Engineering Framework (MEF), supporting migration of workloads and historical data from CDP to Minerva’s Lakehouse and Compute account architecture.
• Validate migrated data products using platform reconciliation tooling, ensuring row counts, schema, and aggregate accuracy between legacy (CDP/Impala) and Minerva (AWS Athena/Lakehouse) sources.

Requirements

• Minimum of 4 years of relevant work experience (typically reflects 5+ years).

Preferred Qualifications

• Cloud Environments: Experience developing data systems on major cloud platforms (AWS, GCP, Azure); hands-on AWS experience strongly preferred given Minerva’s AWS-native architecture.
• Data Architecture: Hands-on experience building modern data architectures, including data lakes, data lakehouses, and data hubs, along with related capabilities such as ingestion, governance, modeling, and observability.
• Data Ingestion: Proficiency in data collection, ingestion tools (Kafka, AWS Glue), and storage formats (Iceberg, Parquet).
• Data Streaming: Experience developing data pipelines with streaming architectures and tools (Confluent Kafka, Apache Flink).
• Data Modeling: Expertise in data transformation and modeling using SQL-based frameworks and orchestration tools (dbt, AWS Glue, Airflow/Astronomer); deep experience with modeling concepts like SCD and schema evolution.
• Data Transformation: Strong background using Spark for data transformation, including streaming, performance tuning, and debugging with Spark UI.
• Programming: Advanced programming skills in Python, Java, Scala, or similar languages; expert-level proficiency in SQL for data manipulation and optimization.
• DevOps: Demonstrated experience in DevOps practices, including code management, CI/CD, and deployment strategies.
• Data Governance: Strong background in data governance principles, including data quality, privacy, and security considerations for data product development and consumption.
• Snowflake & Information Warehouse: Working knowledge of Snowflake, including warehouse/database/schema design and the dbt-Snowflake adapter, for provisioning and serving Minerva data products in the Information Warehouse layer.
• Platform Migration Experience: Prior experience migrating on-premises or legacy platform workloads (e.g., Cloudera, Hadoop, Impala) to a cloud-native lakehouse, including data reconciliation and historical/CDC data loads.
• Engineering Framework & Tooling: Familiarity with Git-based CI/CD delivery for data products (e.g., Vela CI/CD or similar pipeline tooling), Data Product Package structures, and metadata/catalog tools (e.g., Atlan) for lineage and discovery.
• Domain & Source Systems: Exposure to SAP source systems and food/CPG domain data (e.g., supply chain, procurement, commercial/sales) is a plus.

Pay

The expected salary for this position is $90,000 - $155,000. Compensation varies depending on location, certifications, education, and level of experience. This position is eligible for a discretionary incentive award based on company and personal performance.

Benefits

• Comprehensive medical and other benefits, dependent on position and hours worked.
• Minnesota Sick and Safe Leave: accrual of one hour for every 30 hours worked, up to 48 hours per calendar year (unless otherwise provided by law).