Master Data Analyst

As a Master Data Analyst at Halperns Steak & Seafood, your primary responsibilities will include developing and implementing master data business processes, maintaining data integrity, and collaborating with cross-functional stakeholders. You will also be involved in problem-solving, conducting data updates, and providing training materials to ensure staff are well-informed about master data processes.

To be considered for the Master Data Analyst position at Halperns Steak & Seafood, candidates should possess a Bachelor’s Degree in related fields such as Management, Marketing, or Computer Science, along with at least three years of experience in supply chain or a related role. Excellent communication and problem-solving skills, extensive spreadsheet knowledge, and familiarity with SAP S4 or GFS systems are essential.

Halperns Steak & Seafood fosters an amazing culture where what matters to you, matters to us. We emphasize teamwork, respect, and communication, providing a supportive environment for our Master Data Analysts to thrive. We believe our success is linked to the empowerment and satisfaction of our employees, and we are dedicated to ensuring a positive workplace.

As a Master Data Analyst at Halperns Steak & Seafood, you will utilize advanced spreadsheet software, database applications, and other productivity tools. A strong knowledge of SAP S4, SAP MDG, as well as experience with word processing and presentation software, will be beneficial in providing effective data management and reporting solutions.

At Halperns Steak & Seafood, we offer ample opportunities for growth and professional development for our Master Data Analysts. You will have the chance to engage in training sessions, take on complex strategic projects, and contribute to continuous improvement initiatives. Your expertise and input will be valued, giving you a pathway for career advancement.

To ensure the accuracy and integrity of master data, I rely on rigorous validation techniques and regular audits. I maintain a process to check for duplicates and inconsistencies and work closely with cross-functional teams to gather accurate information, ensuring that data updates are well-informed and comprehensive.

In a previous role, I encountered a challenge where multiple data sources conflicted with each other, leading to discrepancies in reporting. I took the initiative to analyze the discrepancies, identify the root causes, and collaborated with various departments to streamline data input processes, resulting in improved data accuracy.

I primarily use advanced spreadsheet tools for data analysis, including complex formulas and macros. Additionally, I have experience with SQL for querying databases and data visualization tools to present my findings clearly and effectively to stakeholders.

When faced with tight deadlines, I prioritize tasks based on urgency and impact. I believe in maintaining open communication with my team to delegate effectively and ensure that we stay aligned. Time management and focus are key, allowing me to produce high-quality work without compromising accuracy.

To communicate complex data findings to non-technical stakeholders, I focus on simplicity and clarity. I tailor my presentations to their level of understanding, using visuals and storytelling techniques to illustrate the implications of the data. This approach ensures that they grasp key insights without getting lost in technical jargon.

I prefer to integrate best practices, such as the CRISP-DM framework, which helps me structure my data analysis process from business understanding to deployment. This systematic approach ensures thorough analysis and provides a reliable foundation for decision-making.

In my previous role, I was part of a cross-functional team tasked with optimizing the supply chain process. I contributed by analyzing data trends that affected inventory levels, which helped the team identify bottlenecks. My insights led to improved coordination between departments, ultimately enhancing efficiency and reducing costs.

My approach to managing and integrating data from multiple sources begins with identifying the key data points required for analysis. I ensure data normalization and standardization to facilitate integration, followed by using data mapping techniques to align disparate sources and ensure consistency across the dataset.

In a previous project, the business requirements shifted mid-analysis due to strategic changes. I had to quickly reassess my findings and pivot my analysis accordingly. By maintaining flexibility and focusing on the new objectives, I successfully delivered a revised report that aligned with the updated goals.

To ensure effective documentation of data processes, I following a structured approach by creating clear, concise guidelines that outline each process step. I incorporate visuals where applicable and regularly update documentation based on process changes to keep all stakeholders informed and aligned.