Data Engineering - Manufacturing Data

Cargill•Atlanta, GA

About The Position

Cargill’s size and scale allows us to make a positive impact in the world. Our purpose is to nourish the world in a safe, responsible and sustainable way. We are a family company providing food, ingredients, agricultural solutions and industrial products that are vital for living. 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 alternative fuel. Our 160,000 colleagues, operating in 70 countries, make essential products that touch billions of lives each day. Join us and reach your higher purpose at Cargill. Job Purpose and Impact The Director, Engineering - Manufacturing Data job leads the team responsible for the execution of the tactical and strategic plans related to design, development and maintenance of robust data systems in the manufacturing domain. This job provides guidance to the team that ensures the efficient processing and availability of data for analysis and reporting.

Requirements

MINIMUM & TYPICAL YEARS OF WORK EXPERIENCE Minimum requirement of 6 years of relevant work experience.
Typically reflects 10 years or more of relevant experience.
Experience in industrial data platforms and time-series data management, including data historians and IoT/OT systems, with proven ability to design architectures that enable edge processing and seamless data integration into cloud environments for advanced analytics and operational optimization.

Nice To Haves

PREFERRED & TYPICAL YEARS OF WORK EXPERIENCE Demonstrated success in driving automation and digital transformation initiatives within manufacturing operations, applying edge computing, data orchestration, and cloud-native technologies to improve process efficiency, asset performance, and business KPIs.
Strong expertise in enterprise data architecture and modeling, leveraging API-first design principles and canonical data models to ensure interoperability, scalability, and governance across heterogeneous systems and applications.

Responsibilities

DATA SYSTEMS: Establishes and maintains robust data systems that support large and complex data products, ensuring reliability and accessibility for partners.
SOLUTIONS DEVELOPMENT: Leads the development of technical products and solutions using big data and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.
DATA PIPELINES: Oversees and guides the design and development of data pipelines that facilitate the movement of data from various sources to internal databases.
DATA INFRASTRUCTURE: Handles the construction and optimization of data infrastructure, resolving appropriate data formats to ensure data readiness for analysis.
DATA FORMATS: Examines and settles appropriate data formats to optimize data usability and accessibility across the organization.
STAKEHOLDER MANAGEMENT: Liaises with partners to understand data needs and ensure alignment with organizational objectives.
DATA FRAMEWORKS: Champions development standards and brings forward prototypes to test new data framework concepts and architecture patterns supporting efficient data processing and analysis and promoting standard methodologies in data management.
AUTOMATED REPORTING SYSTEMS: Leads the creation and maintenance of automated reporting systems that provide timely insights and facilitate data driven decision making.
DATA MODELING: Oversees data modeling to ensure the preparation of data in databases for use in various analytics tools and to configurate and develop data pipelines to move and improve data assets.
TEAM MANAGEMENT: Manages team members to achieve the organization’s goals, by ensuring productivity, communicating performance expectations, creating goal alignment, giving and seeking feedback, providing coaching, measuring progress and holding people accountable, supporting employee development, recognizing achievement and lessons learned, and developing enabling conditions for talent to thrive in an inclusive team culture.