Job Description

Role Purpose

Serves as the analytics subject matter expert for Quality & Continuous Improvement across EMEA, owning the design, development, and evolution of the EMEA-wide performance analytics architecture. Translates complex operational data into strategic insights that drive decision-making at senior leadership level. Acts as the bridge between business stakeholders and data - defining what to measure, how to measure it, and what it means.

Key Responsibilities

Analytics Architecture & Strategy

Design and own the EMEA Quality & CI KPI architecture - defining metrics, hierarchies, calculation logic, and data lineage across all Business Units
Establish standardised KPI definitions (Customer Claims, FPY, COPQ, Warranty, VoC, Supplier Quality) to enable consistent EMEA-wide comparison
Define the analytics roadmap for the function, identifying where advanced analytics, process mining, and AI-enabled approaches can add value
Architect the data model underpinning EMEA Quality & CI reporting - ensuring scalability, accuracy, and maintainability

Insight Development & Stakeholder Advisory

Develop and present monthly operating review analytics to senior leadership - translating data into narrative, identifying root causes, and recommending actions
Partner with BU Quality leaders to define leading indicators and predictive analytics that shift the function from reactive to proactive
Conduct deep-dive analyses on quality trends, warranty patterns, and supplier performance to surface systemic issues
Provide data-driven recommendations to Senior Director and VP-level stakeholders on performance improvement priorities

Platform & Capability Development

Design and build Power BI dashboards and reports that serve as the single source of truth for EMEA Quality & CI performance
Define requirements for data pipelines and integrations (SAP, Snowflake, other source systems)
Evaluate and implement process mining tools (Celonis or equivalent) to identify inefficiencies in quality processes
Drive automation of manual reporting - target 50% reduction in manual effort within 12 months
Develop reusable templates, calculation logic, and self-service analytics capabilities for the broader Quality team

Governance & Data Quality

Own the data governance framework for Quality & CI analytics - defining data ownership, refresh cadences, validation rules, and exception handling
Establish and maintain data quality standards monitor and resolve discrepancies across source systems
Lead 8D maturity tracking methodology - defining scoring criteria and reporting dashboards

Required Skills & Experience

Technical (Must-Have)

Expert-level Power BI development (complex DAX, data modelling, row-level security, deployment pipelines)
Advanced SQL (query optimisation, stored procedures, complex joins across large datasets)
Data modelling and warehouse concepts (star schema, fact/dimension design)
Experience with process mining platforms (Celonis preferred)
Working knowledge of SAP data structures (QM, MM, SD modules)

Technical (Preferred)

Power Platform (Power Automate, Power Apps) for workflow automation
Python or R for statistical analysis
Experience with Snowflake or similar cloud data platforms
AI/ML-enabled analytics (anomaly detection, predictive quality)

Functional

10-15 years of experience in data analytics, business intelligence, or performance management
Demonstrated experience designing KPI frameworks and analytics architectures from scratch
Experience presenting to and advising senior leadership (Director+ level)
Understanding of Quality management systems, manufacturing KPIs, and operational excellence principles
Experience working in global matrix organisations across multiple time zones

Behavioral

Strategic thinking - ability to see the so what behind the data and connect analytics to business outcomes
Stakeholder management - comfortable challenging senior leaders with data and influencing without authority
Ownership mindset - treats the analytics platform as their product, drives quality and continuous improvement unprompted
Structured communication - can distil complex analysis into clear, actionable narratives for non-technical audiences

Education

Bachelor's degree in Engineering, Data Science, Statistics, Computer Science, or Business (required)

Master's degree or MBA (preferred)

Success Measures (First 12 Months)

Single EMEA Quality & CI dashboard live and adopted by all BUs
Standardised KPI definitions agreed and implemented across EMEA
50% reduction in manual reporting effort
Monthly operating review analytics cadence established
8D maturity tracking methodology defined and dashboard deployed
Process mining pilot completed for at least one quality process

Senior Manager Quality Data Analytics