Analytics Product Engineer Arrow Electronics Inc

Purpose of the Role

The Analytics Product Engineer ensures that BIAR s (Business Intelligence, Analytics & Reporting) analytics products are built on scalable, consistent, and reusable data foundations.

This role bridges business requirements and IT-delivered data structures by translating analytical needs into clear data specifications and designing robust semantic models for analytics consumption.

The role complements IT s ownership of ETL and core data modeling by focusing on analytical usability, consistency, and product quality.

Key Responsibilities

Analytics Data & Model Design

• Design and maintain reusable, certified datasets for Power BI and analytics solutions
• Define and implement best practices for analytics data modeling
• Ensure consistent KPI logic and semantic definitions across products
• Optimize performance and usability of analytical datasets

Collaboration with IT

• Translate analytics requirements into structured data needs
• Provide input and feedback on IT-delivered data models from an analytics perspective
• Support integration of MDM (Master Data Management) structures into analytics layers

Standardization & Reusability

• Promote modular, scalable dataset design instead of report-by-report development
• Reduce duplication of calculations and KPI definitions
• Establish quality standards for analytics data products

MDM & Governance Alignment

• Ensure master data is consistently reflected in analytics products
• Align closely with Data Governance on glossary definitions and standards
• Support implementation of certified datasets and trusted data sources

Enablement & Mentoring

• Guide BIAR analysts in modeling best practices
• Raise overall technical maturity within BIAR

What we are looking for:

• 3+ years experience in BI, analytics engineering, or data modeling
• Strong expertise in Power BI datasets and semantic modeling
• Solid understanding of dimensional modeling concepts
• Experience collaborating with centralized IT data teams
• Structured, quality-focused mindset
• Ability to explain technical concepts to business stakeholders

Success Measures (First 12 Months)

• Establishment of certified, reusable datasets for key domains
• Reduced duplication of KPI logic across reports
• Improved performance and scalability of analytics solutions
• Clear working model established with IT and MDM stakeholders