Sr. Data Engineer

Cargill • Wayzata, MN

1d

About The Position

The Senior Professional, Data Engineering job designs, builds and maintains complex data systems that enable data analysis and reporting. With minimal supervision, this job ensures that 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 the ongoing migration off CDP and enabling scalable, governed data solutions for Supply Chain, Procurement & Manufacturing, Commercial Excellence, and LATAM domains.

Requirements

• Minimum requirement of 4 years of relevant work experience.
• Typically reflects 5 years or more of relevant experience
• Advanced programming skills in Python, Java, Scala, or similar languages.
• Expert-level proficiency in SQL for data manipulation and optimization.
• Demonstrated experience in DevOps practices, including code management, CI/CD, and deployment strategies.
• Strong background in data governance principles, including data quality, privacy, and security considerations for data product development and consumption.

Nice To Haves

• Experience developing data systems on major cloud platforms (AWS, GCP, Azure). Hands-on AWS experience strongly preferred given Minerva’s AWS-native 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.
• Demonstrated proficiency in data collection, ingestion tools (Kafka, AWS Glue), and storage formats (Iceberg, Parquet).
• Experience developing data pipelines with streaming architectures and tools (Confluent Kafka, Apache Flink).
• 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.
• Strong background using Spark for data transformation, including streaming, performance tuning, and debugging with Spark UI.
• 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.
• Exposure to SAP source systems and food/CPG domain data (e.g., supply chain, procurement, commercial/sales) is a plus, given FDEAMR’s portfolio scope.
• 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.
• 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.

Responsibilities

• Prepares data infrastructure to support the efficient storage and retrieval of data.
• Examines and resolves appropriate data formats to improve data usability and accessibility across the organization.
• Develops complex data products and solutions using advanced engineering and cloud-based technologies, ensuring they are designed and built to be scalable, sustainable and robust.
• Develops and maintains streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move it to data stores like data lake, data warehouse and others.
• Reviews existing data systems and architectures to identify areas for improvement and optimization.
• Collaborates with multi-functional data and advanced analytic teams to gain requirements and ensure that data solutions meet the functional and non-functional needs of various partners.
• Builds complex prototypes to test new concepts and implements data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.
• Develops automated deployment pipelines improving efficiency of code deployments with fit-for-purpose governance.
• Performs complex data modeling in accordance with the datastore technology to ensure sustainable performance and accessibility.
• Builds and maintains 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.
• Validates migrated data products using platform reconciliation tooling, ensuring row counts, schema, and aggregate accuracy between legacy (CDP/Impala) and Minerva (AWS Athena/Lakehouse) sources.

Benefits

• medical and/or other benefits dependent on the position offered and hours worked
• Minnesota Sick and Safe Leave accruals of one hour for every 30 worked, up to 48 hours per calendar year unless otherwise provided by law

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed