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Ingénieur Data Business Intelligence - Job Opportunity at ZEISS Group

Périgny, France
Full-time
Mid-level
Posted: July 3, 2025
On-site
EUR 45,000 - 55,000 per year. This estimate is based on the mid-level experience requirement, specialized technical skills in data engineering and machine learning, and the location in western France. The role's strategic importance in a global medical device company and the combination of technical and business intelligence responsibilities typically command competitive compensation packages.

Benefits

Opportunity to work within a global leader in optical and optoelectronic industry with strong market position and stability
Professional development opportunities within an international environment with multiple career advancement paths
Exposure to cutting-edge digital transformation initiatives and innovative data strategy implementations
Collaborative and supportive team environment that encourages knowledge sharing and continuous learning
Access to state-of-the-art automated and digital manufacturing facilities representing industry-leading technology
International exposure through coordination with global supply chain teams and stakeholders
Structured recruitment process with clear timeline and feedback mechanisms ensuring transparent candidate experience

Key Responsibilities

Lead the strategic design, development, and maintenance of critical data ingestion and output pipelines that directly impact global supply chain operations across multiple international markets
Transform complex supply chain data into actionable business intelligence tools that drive strategic decision-making for management teams worldwide, directly influencing operational efficiency and customer satisfaction
Architect and maintain robust, scalable data solutions on Azure Databricks and Azure DevOps platforms that support mission-critical supply chain operations for medical device distribution
Develop advanced Python automation scripts and contribute to artificial intelligence initiatives that enhance supply chain performance and predictive capabilities
Manage enterprise-level ETL pipelines using Azure Databricks and Azure Data Factory Studio, ensuring seamless data flow across global operations
Create sophisticated dashboards and advanced reporting solutions using Python Dash and RShiny that provide real-time visibility into supply chain performance metrics
Collaborate directly with international stakeholders to translate complex business requirements into innovative data solutions that drive measurable business outcomes
Implement comprehensive data quality assurance processes that maintain the integrity of critical supply chain data across all operational touchpoints
Lead data modeling initiatives that support advanced analytics and business intelligence requirements across the global organization
Develop and maintain predictive machine learning models that provide risk scoring for stock-out and backorder scenarios, directly impacting customer service levels and operational costs
Provide strategic insights and recommendations through regular performance reporting that influences executive-level decision-making and continuous improvement initiatives

Requirements

Education

Master's degree or Engineering degree

Experience

At least 1 year of equivalent experience as a Data Engineer

Required Skills

Good communication skills including English Ability to collaborate and share knowledge with team members Understanding of data analysis, machine learning, and data visualization Experience with data visualization tools (Power BI, RShiny, Dash etc.) Good knowledge of programming languages: VBA Excel, Python and R Knowledge of classic Machine Learning libraries (Sklearn, Shap etc.) Knowledge of Machine Learning algorithms (RandomForest, Xgboost etc.) Knowledge in software project management (version control etc.) Knowledge in production deployment (Azure DevOps, GitHub etc.) Knowledge of data architecture (SQL etc.)

Certifications

APICS certification would be a plus PMP certification would be a plus Knowledge of SAP ERP would be a plus
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Sauge AI Market Intelligence

Industry Trends

The medical device industry is experiencing unprecedented digital transformation, with supply chain optimization becoming critical for maintaining competitive advantage and ensuring patient care continuity. Companies are increasingly investing in advanced analytics and AI-driven solutions to predict and prevent supply disruptions, particularly in high-stakes medical environments where product availability directly impacts patient outcomes. Healthcare supply chain management is evolving toward predictive analytics and real-time visibility, driven by lessons learned from global disruptions and increasing regulatory requirements. Organizations are prioritizing data-driven decision making to improve inventory management, reduce waste, and ensure compliance with medical device regulations. The convergence of IoT, machine learning, and cloud computing in manufacturing environments is creating new opportunities for supply chain professionals with strong technical backgrounds. Companies in the optical and medical device sectors are particularly focused on implementing Industry 4.0 principles to maintain their competitive edge in highly regulated markets.

Role Significance

Based on the department structure described, this role likely operates within a specialized team of 5-8 data and analytics professionals, collaborating closely with a broader supply chain organization of 30+ professionals. The position involves regular interaction with international stakeholders and cross-functional teams.
This is a strategic mid-level position with significant influence on global operations. The role reports directly to senior management and has responsibility for data solutions that impact decision-making across international markets. The position carries substantial technical leadership responsibilities and serves as a key bridge between technical capabilities and business strategy.

Key Projects

Implementation of predictive analytics models for inventory optimization and demand forecasting across global markets Development of real-time supply chain visibility dashboards that provide executive-level insights into operational performance Integration of machine learning algorithms for risk assessment and automated decision-making in supply chain processes Creation of automated reporting systems that support regulatory compliance and quality assurance in medical device distribution

Success Factors

Technical versatility across multiple platforms and programming languages, with particular emphasis on Python, R, and cloud-based solutions, as the role requires seamless integration of diverse data sources and technologies Strong business acumen combined with technical expertise to translate complex supply chain requirements into actionable data solutions that drive measurable business outcomes Excellent communication skills and cultural adaptability for working effectively with international teams and stakeholders across different time zones and business cultures Proactive problem-solving approach with the ability to identify opportunities for continuous improvement and innovation in data-driven supply chain optimization Deep understanding of regulatory requirements and quality standards specific to medical device manufacturing and distribution

Market Demand

High demand. The intersection of supply chain expertise, data engineering skills, and machine learning knowledge represents a critical skill gap in the market. Medical device companies are actively seeking professionals who can bridge operational excellence with advanced analytics, making this role highly sought after.

Important Skills

Critical Skills

Python programming proficiency is essential as it serves as the primary language for data processing, machine learning model development, and automation scripts that form the backbone of the data engineering infrastructure Azure cloud platform expertise, particularly Databricks and Data Factory, is crucial for managing enterprise-level data pipelines and ensuring scalable, reliable data processing capabilities Machine learning algorithm understanding and implementation skills are vital for developing predictive models that directly impact business operations and strategic decision-making Supply chain domain knowledge provides the business context necessary to translate technical capabilities into meaningful business solutions and operational improvements

Beneficial Skills

SAP ERP system knowledge enhances ability to integrate with existing enterprise systems and understand complex business processes Project management certifications like PMP demonstrate ability to lead complex technical initiatives and coordinate cross-functional teams effectively APICS certification shows deep understanding of supply chain best practices and industry standards, valuable for credibility with business stakeholders Advanced SQL and database architecture skills support the development of more sophisticated data models and reporting solutions

Unique Aspects

Rare combination of medical device industry expertise with advanced data engineering and machine learning applications, providing exposure to highly regulated and technically sophisticated operational environments
Direct impact on global healthcare outcomes through supply chain optimization of critical medical devices, offering meaningful work that contributes to patient care worldwide
Opportunity to work with state-of-the-art manufacturing and data technologies in a newly constructed, digitally advanced facility that represents the future of medical device manufacturing
Integration of traditional supply chain expertise with cutting-edge AI and predictive analytics, positioning for leadership in the evolving landscape of intelligent supply chain management

Career Growth

Career progression to senior roles typically occurs within 3-5 years, with opportunities for rapid advancement based on successful project delivery and demonstrated leadership capabilities. The international scope and technical complexity of this role provide excellent preparation for executive-level positions.

Potential Next Roles

Senior Data Science Manager with expanded team leadership responsibilities and strategic planning authority Supply Chain Analytics Director overseeing multiple data initiatives and cross-functional analytics programs Business Intelligence Architect focused on enterprise-wide data strategy and digital transformation initiatives Global Supply Chain Operations Manager combining technical expertise with broader operational responsibilities

Company Overview

ZEISS Group

ZEISS Group represents one of the world's most prestigious optical and optoelectronic technology companies, with Carl Zeiss Meditec specifically focused on medical technology solutions. The company has established itself as a leader in innovative medical devices, particularly in ophthalmology and microsurgery, with a strong emphasis on research and development and cutting-edge manufacturing processes.

ZEISS maintains a dominant market position in the global optical and medical device industry, with a reputation for precision engineering and innovative technology solutions. The company's strong financial position and continued investment in digital transformation initiatives demonstrate its commitment to maintaining market leadership.
The La Rochelle facility represents a significant strategic investment in France, serving as both a manufacturing center and a global supply chain hub. This location provides excellent access to European markets while supporting worldwide distribution operations, making it a critical component of ZEISS's global operations strategy.
ZEISS promotes a culture of innovation and continuous improvement, with strong emphasis on technical excellence and collaborative problem-solving. The company's focus on digital transformation and Industry 4.0 principles creates an environment where technical professionals can engage with cutting-edge technologies and methodologies.
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