North American Business Intelligence Analyst
Gordon Food ServiceAbout the role
Welcome to Gordon Food Service! We are excited that you are thinking about opportunities with us, and we have an amazing story to share. See below for a quick glance of who we are and the impact you could have on the food service industry. There's a seat at our table for you...
Position Summary:
The North American Business Intelligence Analyst leads the support and development of business intelligence systems and/or solutions for the Merchandising and Marketing Service Center (MMSC) and National Merchandising teams. Works under the direction of the Category Support Manager and collaborates with enterprise Technical Leads, Sr./Intermediate BI Solutions Engineers, and the greater GTS organization on business intelligence projects. Leads the creation of business intelligence solutions for the MMSC and National Merchandising teams and may collaborate with contractors in the development of delegated tasks, data integration, and assumes support of the ongoing performance of created solutions. Responsible for continuing education in Business Intelligence domain-specific concepts and technologies that drive team success.
What you will do:
Implements standard reporting solutions for internal customers across the MMSC and National Merchandising teams, creating visually rich reports and dashboards.
Maximizes product margin results through leading and/or assisting with the development of supply-side predictive analytic tools and analytic applications for accessing and analyzing information in the Enterprise Data Warehouse and Data Lake.
Optimizes reporting and business processes by leading the development and use of data for Robotic Process Automation (RPAs) in automating Category and Regional business tasks.
Collaborates with the GTS initiatives in implementing MMSC point solutions with approved analytical tools.
Identifies opportunities to improve processes and strategies with technology solutions.
Identifies IT/Business Intelligence development needs in order to improve and streamline business processes.
Performs data quality validation and data profiling to ensure a high level of information integrity.
Assists with the development and testing of programs to extract, cleanse, transform, and load from source systems into appropriate data analysis tools.
Helps ensure consistent use of Gordon Food Service Common Business Language during the development of analytic solutions.
Provides support to users who develop reporting for their own use.
Creates and maintains documentation including requirements, design, and user instructions.
Identifies best practices both within Gordon Food Service and across the industry form implementation.
Performs other duties as assigned.
When you will work:
Monday through Friday, 8:00am - 5:00pm.
Hybrid Work Schedule: 4 days in office, 1 day from home.
What you'll bring to the table:
At least five years prior experience in business intelligence, advanced predictive analytics, machine learning, or a combination of these areas.
Bachelor's degree in Computer Science, Information Technology, Data Analytics, or related field.
Must have good written, verbal, organizational and communication skills as well as problem-solving capabilities.
Must have the ability to multitask, prioritize and be able to work independently or within a team environment.
Ability to do self-service data discovery using modern analytic tool sets.
Proficient in one or more program languages, operating systems, and databases.
Must have strong analytical and troubleshooting skills.
Knowledge of business intelligence and data warehouse principles preferred.
Ability to develop solutions to complex problems that require the regular use of ingenuity and innovation, and ensure solutions are consistent with organization objectives.
Familiarity with modern analytic platforms that provide classification, predictive, and prescriptive functionality.
Prefer experience with SAP’s ERP platform.
Preferred : Knowledge of ETL data load tools, Google Cloud Platform Big Data Technologies, statistical techniques and predictive analyt
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