Consultant, Data and Analytics (Data Engineer)

Cargill

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Job Description

Job Purpose and Impact

The Professional, Data & Analytics Reporting job is responsible for collecting, processing, and analyzing moderately complex datasets to generate actionable insights and builds detailed reports and dashboards using specifics tools. With limited 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 supports the effective presentation of data findings to partners to meet business objectives.

Key Accountabilities

DATA COLLECTION & ANALYSIS: Gathers, processes, prepares, and analyzes moderately complex datasets to extract significant insights, develop and maintain automated reporting systems to streamline data analysis.
REPORTING & VISUALIZATION: Implements detailed reports and dashboards using various tools, designs and completes data visualizations to communicate moderately complex data clearly.
STATISTICAL ANALYSIS: Supports statistical analysis execution to identify trends, patterns, and anomalies in data using statistical software and programming languages for data manipulation and analysis.
PROCESS IMPROVEMENT: Implements found opportunities to improve data collection and reporting processes and applies standard methodologies for data management and reporting.
COLLABORATION: Works closely with multi-functional teams to support data needs, value opportunities and delivers solutions in partnership with digital technology and data engineering teams to help ensuring data integrity and accuracy.
DATA ANALYSIS: Conducts moderately complex data analyses to uncover trends, patterns, and actionable insights for decision making.
QUALITY ASSURANCE & DATA VALIDATION: Performs moderately complex reports and analyses in support of the accuracy, consistency, and security of data.

Qualifications

Have a Bachelor's degree with minimum 4 years of professional experience.
Have 4 years of experience in Data Engineering, including building and maintaining data pipelines.
Have strong proficiency in SQL
Hands-on experience in Python.
Solid experience in data modelling.

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