Process Mining Analyst

As a Process Mining Analyst at ALDI, your primary responsibilities include conducting process-related analytics and developing data-driven solutions to enhance business processes across various functions like Buying, Supply Chain, and IT. You'll focus on creating dashboards, managing projects, engaging with stakeholders to gather insights, and implementing process efficiency solutions that align with the PM&A framework.

To qualify for the Process Mining Analyst role at ALDI, you should have proven experience as a Technical Analyst within a large commercial organization, strong skills in SQL and Python, and proficiency in reporting tools such as Tableau or Power BI. Ideally, you should also have experience with SAP Retail, data mining systems like Celonis, and a background in the FMCG industry, particularly focusing on process analytics.

ALDI supports the professional development of Process Mining Analysts through access to continuous learning opportunities, generous leave policies for personal growth, and wellness programs that promote wellbeing. Additionally, the company's recognition as an Employer of Choice highlights its commitment to fostering a supportive workplace culture.

Process Mining Analysts at ALDI utilize various tools such as SQL for data manipulation, Python for automation tasks, and platforms like Celonis for process mining analytics. They also use reporting tools like Tableau or Power BI to develop dashboards that effectively communicate insights to stakeholders across the organization.

A Process Mining Analyst at ALDI can expect numerous career growth opportunities within the National IT department. As you build expertise in analytics and project management, you may progress to senior analyst roles or even managerial positions, engaging in more strategic projects and influencing key business decisions across the organization.

When answering this question, emphasize your hands-on experience with Celonis or similar tools, detailing specific projects where you used the software to enhance process visibility and efficiencies. Discuss the impact your analysis had on decision-making and how you collaborated with stakeholders to implement improvements.

Respond by outlining your strategy for understanding stakeholders' needs, which includes conducting meetings, creating surveys for feedback, and maintaining open communication. Highlight a specific example where effective engagement led to successful project outcomes, showing your ability to bridge the gap between technical and non-technical stakeholders.

Discuss your ability to prioritize tasks using techniques such as the Eisenhower Box or Kanban system. Provide examples of how you've balanced multiple projects, met deadlines, and avoided burnout, illustrating your time management skills are crucial for the busy role of a Process Mining Analyst.

Share a specific project where your data analysis led to measurable process improvements. Discuss the challenges faced, how you leveraged data to identify key insights, the actions taken, and the tangible results achieved, illustrating your analytical problem-solving skills.

Discuss your proficiency in reporting tools like Tableau and Power BI. Explain the factors you consider when selecting a tool—such as user-friendliness, data integration capabilities, and specific project requirements—and share an example of how your choice positively influenced project outcomes.

Emphasize the importance of data governance and compliance in your analytical processes. Describe how you stay informed about relevant regulations, implement systematic data management practices, and protect sensitive data while conducting analyses, demonstrating your commitment to responsible data use.

When addressing this question, provide examples of how you've utilized SQL for tasks like querying databases, maintaining data integrity, and generating reports. Share specific scenarios where your SQL skills led to valuable insights or process efficiencies within your previous projects.

This is an opportunity to showcase your industry knowledge. Discuss challenges such as maintaining data accuracy, integrating disparate data sources, or adapting to rapid market changes. Provide insights on potential strategies the grocery industry could implement to overcome these challenges, emphasizing the role of analytics.

Explain your methodology for data analysis, which includes hypothesis testing, process mapping, and reviewing KPIs. Share a specific case where you identified significant pain points and how your findings facilitated process improvements or strategic planning.

For this question, tie your response to ALDI’s mission, values, and your personal and professional goals. Mention your enthusiasm for using data to drive efficiency in the retail space and how you want to contribute to ALDI's commitment to providing quality products at low prices, emphasizing alignment with the company culture.