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Reimagining what's possible for food and agriculture
The Role
Design, build, and maintain scalable batch and streaming data platforms and pipelines (Snowflake, Kafka/Pulsar). Develop production-grade Python ETL/ELT, data models, automated deployments, and ensure security, governance, performance, reliability, and GenAI enablement. Partner with analytics and business stakeholders to deliver robust data products.
Summary Generated by Built In
Job Purpose and Impact
Key Accountabilities
Qualifications
- 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.
Key Accountabilities
- DATA INFRASTRUCTURE: Prepares data infrastructure to support the efficient storage and retrieval of data.
- DATA FORMATS: Examines and resolves appropriate data formats to improve data usability and accessibility across the organization.
- DATA & ANALYTICAL SOLUTIONS: 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.
- DATA PIPELINES: 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 to data stores like data lake, data warehouse and others.
- DATA SYSTEMS: Reviews existing data systems and architectures to identify areas for improvement and optimization.
- STAKEHOLDER MANAGEMENT: Collaborates with multi-functional data and advanced analytic teams as well as with business teams to gain requirements and ensure that data solutions meet the functional and non-functional needs of various partners.
- DATA FRAMEWORKS: Builds complex prototypes to test new concepts and implements data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.
- AUTOMATED DEPLOYMENT PIPELINES: Develops automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.
- DATA MODELING: Performs complex data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.
Qualifications
- Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.
- TECHNICAL SKILLS REQUIRED:
- Data Platform Design - Designing scalable ELT data platforms on Snowflake supporting batch and real-time workloads
- Advanced Python Engineering - Building production-grade Python pipelines and reusable data frameworks, with working knowledge of .NET services and integrations
- Snowflake & Relational Database Expertise - Deep knowledge of Snowflake architecture, advanced SQL, and experience working with Oracle, SQL Server, and PostgreSQL
- Batch & Real-Time Processing - Designing and operating reliable batch and streaming / real-time data pipelines using Apache Kafka and Apache Pulsar
- Performance & Cost Optimization - Optimizing Snowflake queries, warehouse usage, and Python workloads for efficiency and scale
- Security & Governance - Implementing access controls, data protection, and secure data-sharing patterns across data platforms
- Reliability & Data Quality - Ensuring pipeline resilience, monitoring, and data quality across critical datasets
- GenAI Enablement - Enabling GenAI use cases through high-quality data pipelines, including preparation of structured and unstructured data, embeddings, and integration with OpenAI (e.g., RAG-style workflows)
PREFERED COMPETENCIES- Proven experience working in the Trading and / or Finance industry
- Proven experience with MS Power BI and Tableau
Skills Required
- Minimum 4 years relevant work experience
- Design scalable ELT data platforms on Snowflake supporting batch and real-time workloads
- Advanced Python engineering for production-grade pipelines and reusable data frameworks
- Working knowledge of .NET services and integrations
- Deep knowledge of Snowflake architecture and advanced SQL
- Experience with relational databases: Oracle, SQL Server, PostgreSQL
- Designing and operating batch and streaming/real-time data pipelines using Apache Kafka and Apache Pulsar
- Performance and cost optimization for Snowflake queries, warehouses, and Python workloads
- Implementing security, access controls, data protection, and governance across data platforms
- Ensuring pipeline reliability, monitoring, and data quality across critical datasets
- GenAI enablement: preparing structured/unstructured data, embeddings, and OpenAI/RAG-style integrations
- Automated deployment pipelines and code deployment governance
- Proven experience in Trading and/or Finance
- Experience with MS Power BI and Tableau
What the Team is Saying
Gaby
Data Engineering Lead
Landon
North America Service Assurance Manager
Navita
Software Engineering Senior Supervisor
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William Orgertrice
Data Engineer
Kayode D.
Principal Data Engineer
Patricia
Supply Chain Learning & Development and Digital Support Lead
Heather W.
Software Engineer
Kristen K.
Factory of the Future Digital Product Manager
Shrey B.
Senior Software Engineer
Madhuri P.
Senior Data Scientist
William Orgertrice
Data Engineer — Data Function, Platforms and Product Engineering
Navita S.
Software Engineering Senior Supervisor
Heather W.
Software Engineer
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Cargill Compensation & Benefits Highlights
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Retirement Support — Two-layer retirement program combines a 401(k) match (100% on the first 3%, 50% on the next 2%) with an employer-funded Employee Retirement Account of roughly 2.5–7% based on age and service. Match is delivered quarterly in company stock and the ERA adds long-term value through additional employer contributions.
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Leave & Time Off Breadth — PTO starts at 15 days and scales to 30 days with tenure, governed by a clear June 1–May 31 cycle. This structured ladder provides predictable time away as service grows.
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Parental & Family Support — Paid family leave offers up to 6 weeks to bond with a new child and 4 weeks to care for a family member or qualifying military needs. Additional supports such as Bright Horizons childcare solutions and Milk Stork reinforce family care.
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The Company
What We Do
We are a family company providing food, ingredients, agricultural solutions and industrial products to nourish the world in a safe, responsible and sustainable way. We connect farmers with markets so they can prosper. We connect customers with ingredients so they can make meals people love. And we connect families with daily essentials— from eggs to edible oils, salt to skincare, feed to flooring. By providing customers with products that are vital for living, we help businesses grow, communities prosper and consumers live well in their daily lives.
Why Work With Us
The decision to join Cargill can open the door to a world of possibility. As part of our Digital, Technology & Data team, you’ll get to be part of a large and diverse group full of unique perspectives united by a common, higher purpose while building a rewarding career full of opportunity, growth and the satisfaction of knowing your work matters.
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Cargill Teams
Cargill Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Typical time on-site:
Not Specified
