Data Engineer

As a Data Engineer at Fives North American Combustion, Inc, you will play a crucial role in leveraging data to enhance our engineering and manufacturing processes, improve product quality, and drive operational efficiency. You will collaborate with cross-functional teams to extract, analyze, and visualize data, providing valuable insights that will guide our strategic decisions. The successful candidate will possess a combination of analytical skills, technical proficiency, and industry knowledge to thrive in this role.

Duties & Responsibilities: All duties and responsibilities are essential functions of the position. Other duties and responsibilities may be assigned.

• Data Collection and Integration: Gather, clean, and integrate data from various sources, including production databases, sensor data, and external datasets.
• Data Analysis: Conduct exploratory data analysis to identify patterns, trends, and anomalies.
• Perform statistical analysis and hypothesis testing to derive meaningful insights.
• Data Visualization: Create informative and visually appealing dashboards and reports using tools like Tableau, Power BI, or Python libraries.
• Predictive Modeling: Develop predictive models to forecast manufacturing performance, quality, and operational outcomes.
• Root Cause Analysis: Investigate production issues and quality concerns by analyzing data to identify root causes and recommend corrective actions.
• Performance Monitoring: Establish and maintain key performance indicators (KPIs) to track manufacturing and engineering metrics. Generate regular reports to communicate performance trends to stakeholders.
• Cross-functional Collaboration: Collaborate with engineering, manufacturing, and quality assurance teams to understand their data needs and provide analytical support
• Continuous Improvement: Suggest process improvements and optimizations based on data analysis.
• Data Security and Compliance: Ensure data security and compliance with relevant regulations, such as GDPR or industry-specific standards. Build and maintain the infrastructure for collecting, storing, and processing data
• Design, develop, and manage data pipelines, ETL processes, and data warehouses.
• Work to optimize data processing and storage for both structured and unstructured data.

Profil

• Proven experience as a Sr. Data Analyst and/or Data Engineer in an engineering or manufacturing environment.
• Proficiency in data analysis tools and programming languages, such as Python, R, SQL, and Excel.
• Strong data visualization skills with tools like Tableau or Power BI.
• Excellent knowledge of statistical analysis and machine learning techniques.
• Ability to communicate complex findings and insights effectively to both technical and non-technical stakeholders.
• Strong problem-solving skills and attention to detail.
• Familiarity with manufacturing processes and quality control is a plus.
• Requires experience with enterprise ERPs (SAP S4HANA, Oracle EBS), CRMs (Salesforce, Hubs