Job Description
Job Summary:
We are seeking a results-driven Data Analyst to join our Plant Controlling team and spearhead our analytics and automation initiatives. This is not a traditional reporting role; you will be the catalyst for transforming our data landscape. You will architect and build robust ETL pipelines, develop sophisticated analytical models, and create interactive visualizations that provide unprecedented insight into our manufacturing operations.
This role is a critical business partner to plant leadership, focused on leveraging data to drive strategic decisions in production efficiency, cost management, and inventory optimization. If you are passionate about building scalable data solutions, automating complex processes, and using data science to solve real-world business problems, this is the perfect opportunity to make a tangible impact in a world-class manufacturing environment.
Key Responsibilities:
- Data Engineering & Automation:
* Design, build, and maintain automated ETL pipelines (using tools like Alteryx, Power Query, Python) to extract and consolidate large datasets from SAP (CO, FI, MM) and other plant systems into standardized models for analysis.
* Develop and deploy automation scripts (Python, VBA) to streamline financial calculations, month-end closing activities, and reporting workflows, significantly reducing manual effort and improving accuracy.
* Architect and implement robust data reporting frameworks, ensuring data integrity and creating a "single source of truth" for key plant metrics.
- Advanced Analytics & Visualization:
* Develop and deploy interactive dashboards in Power BI and/or Tableau to visualize KPIs for executive stakeholders, including production efficiency, cost variances, inventory health, and cash flow trends.
* Perform comprehensive variance, trend, and ratio analysis to support FP&A reviews, providing clear commentary on deviations from budget and forecast.
* Write and optimize complex SQL queries to support deep-dive analytics into inventory, expenses, and operational performance.
- Inventory & Cost Controlling:
* Conduct in-depth analysis of inventory levels, turnover, and aging to identify slow-moving and obsolete (SLOB) risks and opportunities for optimization.
* Support and enhance the physical inventory and cycle counting programs by automating data preparation, discrepancy analysis, and results reporting.
* Analyze manufacturing cost variances (material, labor, overhead) to identify root causes and partner with operations to develop corrective action plans.
- Predictive Modeling & Process Improvement:
* (Opportunity for Growth) Implement foundational time-series or regression models (using Python/R) to forecast key metrics like production volume, scrap rates, or inventory needs.
* Act as a subject matter expert on data tools and methodologies, training junior team members and promoting a data-driven culture within the plant.
* Continuously identify and implement process improvements by leveraging technology to enhance the capabilities and efficiency of the controlling function.