Data Engineer Machine Learning and Data Visualization

Job Title

Job Description

Required Education
• BS Degree (Bachelor of Science) required
• Master's Degree is acceptable as an alternative
• Associate Degree + 5 years of experience accepted in lieu of BS
• Internships do not count toward experience
• Minimum 2+ years of experience required (with BS Degree)

Required Skills
• Python (expertise required)
• SQL (advanced querying and data manipulation)
• ETL/ELT development
• Data pipeline design and implementation
• Data warehousing concepts and implementation
• Data quality management
• Data modeling
• Power BI expertise (dashboards, reports, analytics)
• Tableau expertise (alternative to Power BI)
• Executive reporting and data-driven storytelling
• Cloud platform experience (AWS / Azure / GCP)
• Modern data warehouse experience (Snowflake / Big Query)
• Statistical analysis
• Machine learning algorithms
• Feature engineering
• NLP and text analytics
• Supply chain concepts
• Capacity planning concepts
• Inventory management concepts

Soft Skills (Required)
• Strong business acumen
• Strong problem-solving skills
• Excellent communication skills
• Excellent stakeholder management skills
• Ability to partner with IT teams
• Ability to translate business requirements into technical solutions

Core Job Responsibilities
• Support development, testing, and delivery of BI solutions for supply chain and capacity planning
• Gather and document business requirements
• Create functional requirement documents
• Perform validation testing
• Support successful system implementations
• Serve as subject matter expert and data/reporting owner for key business processes
• Respond to inquiries from internal stakeholders and business partners
• Support daily production and reporting processes across multiple platforms
• Develop, maintain, and enhance Power BI reports, dashboards, and analytics solutions
• Troubleshoot complex system and data issues
• Identify root causes and implement high-quality solutions
• Lead or contribute to medium- and large-scale projects
• Collaborate with cross-functional business and IT teams
• Work with global teams (international collaboration)