Analytics Engineer

Job Description

Pluxee is a global player in Employee Benefits and Engagement that operates in 28 countries. We help companies attract, engage, and retain talent through a broad range of solutions across Meal & Food, Well‑being, Lifestyle, Reward & Recognition, and Public Benefits. With more than 5,600 team members and a B2B2C ecosystem of 500,000 clients, 37 million+ consumers, and 1.7 million+ merchants, we are committed to creating a positive impact on local communities, supporting well‑being at work, and protecting the planet.

Reporting to the Hub Lead Data Engineer, the Hub Analytics Engineer is a member of the Hub Data Analytics team. This role blends Data Analyst and Data Engineer responsibilities, handling the entire data lifecycle—from ingestion to reporting and analysis. Your work will enable dashboards, self‑service analytics, and AI applications across the organization, driving commercial strategy and decision‑making on 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, using Azure Data Factory pipelines, PySpark, Python, REST APIs, SQL & NoSQL databases, batch and files, with various latencies (from batch to real‑time).
• Orchestrate jobs following DAG principles.
• Ensure data flows are reliable, documented, and easy to maintain.
• Design optimized tables (distribution and indexing) for maximum performance.
• Implement proven patterns such as Slowly Changing Dimensions (SCD) or Data Vault for historization and flexibility.
• Use established designs like Star Schema or relational models to facilitate analysis and reporting.
• Document transformations and models comprehensively to ensure traceability and understanding by stakeholders.
• Proficiency with Business Intelligence tools (Power BI) to ensure consistency between models and reporting.

Data Analyst closely embedded with Business teams

• Actively participate in discussions with business teams to understand specific data needs and decision‑making processes.
• Translate these requirements into concrete solutions, ensuring the models delivered meet business objectives.
• Conduct thorough data exploration to understand relationships between tables and identify relevant data sources, designing data models that support business goals.
• Validate data quality and consistency against business information by testing and auditing data to meet business rules and reliability expectations.
• Facilitate iterative development of data flows to ensure business expectations are understood and models/data processes are adjusted based on continuous feedback.

Data Analytics Platform User

• Understand the data platform architecture and the purpose of each Azure resource.
• Ensure compliance with data protection law (PII encryption).
• Monitor data ingestion jobs.
• 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.
• Read and understand code developed by other members to allow maintenance and evolution (reverse‑engineering).
• Maintain and update project boards with accurate, up‑to‑date information, providing a clear view of project progress and milestones.

Data Science skills (as a plus)

• Proficiency in Python or R for advanced data analysis and modelling.
• Experience in developing and deploying predictive models (regression, classification, time series forecasting) to address business challenges.
• Knowledge of statistical methods for data analysis, hypothesis testing, A/B testing, and understanding of model evaluation metrics.
• Familiarity with neural networks and deep learning techniques (if applicable).

This is your chance to be part of a dynamic team where your expertise in data platform management and project execution will drive innovation and contribute significantly to our business success.

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, including querying and procedures.
• Advanced knowledge of relational and dimensional database management (indexing, distribution choices).
• Experience in at least one of C#, Python, or PySpark.
• Data modelling for analytical purposes and for OLTP databases.
• Cloud computing knowledge: 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 experience (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).
• Good understanding of company business.
• Ability to understand business needs and co‑build solutions.
• Excellent communication skills, especially with non‑technical stakeholders.
• Curiosity and proactive problem‑solving approach.
• Fluency in English is 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.

Joining Pluxee as a Hub Analytics Engineer offers an exciting opportunity to be at the forefront of our strategic initiatives. As a collaborative and innovative team, we value your expertise in driving successful project execution and making a significant impact on the organization’s growth and success.