Senior Consultant, Data Analytics and Reporting

cargill

23h

About The Position

Cargill is committed to providing food and agricultural solutions to nourish the world in a safe, responsible, and sustainable way. Sitting at the heart of the supply chain, we partner with farmers and customers to source, make and deliver products that are vital for living. Our 155,000 team members innovate with purpose, providing customers with life’s essentials so businesses can grow, communities prosper, and consumers live well. With over 160 years of experience as a family company, we look ahead while remaining true to our values. We put people first. We reach higher. We do the right thing—today and for generations to come.Job Purpose and Impact
The Senior Consultant, Data & Analytics Reporting job is responsible for collecting, processing, and analyzing complex datasets to generate actionable insights and builds detailed reports and dashboards using specifics tools. With minimal supervision, this job collaborates with cross functional teams to ensure data accuracy and integrity performing data and statistical analysis using various programming languages. This job plays a key role in effectively presenting data findings to partners to meet business objectives. 

Requirements

• Minimum requirement of 4 years of relevant work experience.
• Typically reflects 5 years or more of relevant experience.

Nice To Haves

• PRODUCT BACKLOG: Managing a product backlog and prioritizing features using value-driven frameworks.
• PRODUCT DISCOVERY: Running discovery sessions, gathering requirements, and writing user stories.
• AGILE: Experience with Agile or product operating models, including Scrum and Kanban.
• STORYTELLING: Excellent communication and storytelling skills, with the ability to present insights to executives and non-technical audiences.
• DATA GOVERNANCE: Knowledge of data governance practices, including metadata, lineage, quality frameworks, and privacy/security standards.
• DATA MODELING: Hands-on experience with data modeling (Kimball, star, semantic models) and designing scalable analytical datasets.
• DATA ENGINEERING: Familiarity with modern data engineering and analytics technologies, such as SQL, Python, Spark, dbt, and cloud-native data services (Azure, AWS).
• AI AND ML: Familiarity with ML/AI workflows, including model evaluation, feature engineering, and MLOps concepts.

Responsibilities

• DATA COLLECTION & ANALYSIS: Captures, processes, prepares, and analyzes complex datasets to extract significant insights, develop and maintain automated reporting systems to streamline data analysis.
• STAKEHOLDER MANAGEMENT: Cultivates and maintains positive partners relationships to understand their data needs, provides insights and finds improvement opportunities, and ensures reporting solutions address key objectives.
• REPORTING & VISUALIZATION: Builds detailed reports and dashboards using various tools, designs and implements data visualizations to communicate complex data clearly.
• STATISTICAL ANALYSIS: Performs statistical analysis to identify trends, patterns, and anomalies in data using statistical software and programming languages for data manipulation and analysis.
• PROCESS IMPROVEMENT: Identifies opportunities to improve data collection and reporting processes and implements standard methodologies for data management and reporting.
• COLLABORATION: Works closely with cross functional teams to understand data needs, value opportunities and delivers solutions in partnership with digital technology and data engineering teams to ensure data integrity and accuracy.
• LITERACY: Coaches and advises to mature data consumption and analytics capabilities.
• DATA ANALYSIS: Conducts complex data analyses to uncover trends, patterns, and actionable insights for decision making.
• QUALITY ASSURANCE & DATA VALIDATION: Ensures the accuracy, consistency, and security of data across all reports and analyses.

What This Job Offers

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