Analytics Engineer

At Pluxee, we shape the world of employee benefits and engagement by bringing to life a personalized and sustainable employee experience, at work and beyond.

Permanent Regular Job Description: Pluxee is a global player in Employee Benefits and Engagement that operates in 28 countries. Pluxee helps companies attract, engage, and retain talent thanks to a broad range of solutions across Meal & Food, Well‑being, Lifestyle, Reward & Recognition, and Public Benefits. Powered by leading technology and more than 5,600 engaged team members, Pluxee acts as a trusted partner within a highly interconnected B2B2C ecosystem made up of more than 500,000 clients, 37 million+ consumers and 1.7 million+ merchants. Conducting business for more than 45 years, Pluxee is committed to creating a positive impact on local communities, supporting well‑being at work for employees, and protecting the planet.

Role Overview

Reporting to the Hub Lead Data Engineer, the Hub Analytics Engineer is a member of the Hub Data Analytics team. The role is a fusion of Data Analyst and Data Engineer responsibilities, handling end‑to‑end projects. The Analytics Engineer plays a crucial role in understanding business requirements, designing optimized data flows, and delivering robust and high‑performance analytical models to improve commercial strategies and decision‑making across multi‑domain projects.

Mission & Responsibilities

• Expert in Design and Management of Data flows – develop and maintain robust, cost‑efficient, high‑performance data pipelines end‑to‑end, mixing technologies such as Azure Data Factory pipelines, PySpark, Python, Rest API, SQL & NoSQL databases, batch and files with different latencies (from batch to real‑time)
• Orchestrate jobs following DAG principles, ensuring reliability, documentation and ease of maintenance
• Design optimized tables (choosing the right distribution, indexing) to ensure maximum performance
• Implement proven patterns such as Slowly Changing Dimensions (SCD) or Data Vault for data historization or flexibility
• Adopt established designs like Star Schema or relational models to facilitate analysis and reporting
• Document transformations and models comprehensively for traceability and stakeholder understanding
• Proficiency with Business Intelligence tools (Power BI) to maintain consistency between models and reporting
• Actively participate with business teams to understand data needs and decision‑making processes, translating requirements into concrete, business‑aligned solutions
• Conduct data exploration to understand relationships among tables, identify relevant sources, and design data models that support business goals
• Validate data quality and consistency against business rules and expectations, testing, auditing, and managing errors or inconsistencies
• Facilitate iterative development of data flows, ensuring business expectations are understood and models or processes adjusted based on continuous feedback
• Understand the data platform architecture and purpose of each Azure resource, ensuring compliance with data protection law (PII encryption)
• Monitor data ingestion jobs and develop, test, and deploy code and jobs within a DevOps framework, managing branches, pull requests, and test environments
• Collaborate with other Analytics Engineers and Data Engineers, following Hub team guidelines and best practices
• Maintain and update project boards with accurate, up‑to‑date information to provide a clear view of project progress and milestones

Additional Qualifications

• Data Science skills (as a plus): proficiency in Python or R for advanced analysis and modeling; experience with predictive models (regression, classification, time series forecasting); knowledge of statistical methods, hypothesis testing, A/B testing, and evaluation metrics; familiarity with neural networks and deep learning techniques if applicable

Profile, Experience & key Competencies

• Master’s degree in computer science/data engineering/statistical engineering/information processing or equivalent
• At least 2 years building and managing ETL and ELT processes
• Strong SQL skills: querying and procedures
• Advanced knowledge of relational and dimensional database management (indexing, distribution choices)
• Experience with at least one of C#, Python or PySpark
• Data modeling for analytical purposes & OLTP databases
• Cloud computing: storage, serverless, API – Azure is a plus
• Distributed computation with Spark
• Good understanding of Python applied to Machine Learning
• DevOps principles with CI/CD (Azure DevOps) and infrastructure as code
• REST API: OAuth, Swagger, backend services
• Real or near real‑time data process design and implementation
• Advanced knowledge of data lake and data warehouse for analytical and operational purposes
• Experience working transversally in an international company and in an agile organization
• Agile Project Management knowledge (tracking on Azure Boards)
• Understanding of company business and ability to co‑build solutions that meet those needs
• Excellent communication skills, especially with non‑technical stakeholders
• Curiosity and proactive problem‑solving approach
• Fluency in English required
• Ability to work autonomously
• Team spirit and engagement in projects

Working Conditions

This is a full‑time role. Hybrid: on site and work from home according to hosting country policy.

Benefits

• Join an inclusive team
• Work at the heart of the community alongside 5,000 experts across 29 countries – we embrace diversity and value uniqueness, fostering a workplace where everyone can thrive
• Bring new digital experiences and moments of connection to millions of people, turning inspiration into possibility
• Make a positive impact by touching millions of lives and creating meaningful change, supporting commitments to diversity, sustainability and local economies
• Grow with us – get the support needed to take meaningful steps in your career, whether you’re balancing work and life or learning new skills

We welcome applicants from all backgrounds and are an equal opportunity employer.