Vates is a French software company specializing in virtualization, offering a credible alternative to proprietary solutions on the market. Our Vates VMS solution enables companies to manage their IT infrastructures in a simple, efficient, and controlled way.

We are looking for a Data Analyst to help us turn this data into a reliable, understandable and usable foundation for the company.

You will work at the intersection of business intelligence, data modeling and data engineering. Your role will be to transform data coming from our operational systems into well-structured, tested and documented datasets that can be confidently used for reporting, analysis and operational processes.

Your Responsibilities:

Data Warehouse & Modeling

- Build and maintain data models in our Data Warehouse.

- Transform raw data from operational systems into clean, consistent and reusable datasets.

- Design analytical models and data marts supporting Sales, Finance, Marketing, Customer Success and other business functions.

- Improve existing models as business processes and requirements evolve.

- Ensure that models remain understandable, maintainable and appropriately structured as the Data Warehouse grows.

Data Quality

- Define and implement automated data quality checks.

- Identify missing, inconsistent, duplicated or anomalous data.

- Investigate discrepancies between systems and reports.

- Trace data issues back to their source and help address their root causes.

- Implement reconciliation mechanisms for critical business data.

- Make data quality measurable and visible rather than relying on manual validation.

Business Metrics & Reporting

- Work with business stakeholders to understand their reporting and analytical needs.

- Translate business concepts into precise and reproducible data definitions.

- Define and maintain shared metrics and KPIs.

- Build and maintain dashboards and reports.

- Ensure that the same business concept is calculated consistently across reports and teams.

- Help users understand the meaning, scope and limitations of the data they use.

Typical topics may include revenue, ARR, MRR, churn, sales pipeline, customers, partners, subscriptions, contracts, billing and product usage.

Data Integration

- Work with data coming from multiple internal and external applications.

- Contribute to the design of reliable ingestion and transformation pipelines.

- Understand how data flows between operational systems, the Data Warehouse and downstream consumers.

- Work with application and integration developers when changes to source systems or data flows are required.

- Participate in defining appropriate interfaces and data contracts between systems.

Documentation & Data Governance

- Document datasets, transformations, metrics and important business definitions.

- Maintain visibility over data lineage and dependencies.

- Contribute to naming conventions, modeling standards and data engineering practices.

- Help identify authoritative sources for key business information.

- Participate in improving the consistency of shared entities such as customers, organizations, products and subscriptions across systems.

Required Skills:

- Mastering SQL to query, extract, filter, join and transform data from relational databases.

- Analyzing and manipulating data using Excel, Google Sheets, Python or R.

- Using Python and libraries such as Pandas, NumPy and Matplotlib for data analysis and visualization.

- Cleaning and preparing data by identifying and correcting missing, duplicated, inconsistent or inaccurate data.

- Performing statistical analyses to identify trends, correlations, patterns and anomalies.

- Building dashboards and reports using Business Intelligence tools such as Power BI, Tableau or Looker.

- Creating data visualizations to present complex information in a clear and accessible way.

- Defining and monitoring KPIs to measure business performance and support decision-making.

- Understanding relational databases and concepts such as tables, relationships, primary keys, foreign keys and joins.

- Collecting, combining and transforming data from multiple internal and external sources.

- Automating data analysis and reporting processes using SQL, Python or dedicated automation tools.

- Ensuring data quality and consistency throughout the analysis process.

- Interpreting analytical results and translating data into actionable business insights.

- Documenting data sources, queries, methodologies and analytical processes to ensure transparency and reproducibility.

- Managing ETL/ELT processes to extract, transform and load data from different sources.

- Applying data modeling principles to structure data efficiently for analysis and reporting.

- Working with APIs and various data formats such as CSV, JSON, XML and Parquet.

- Using Git and version control systems to manage scripts, analyses and collaborative projects.

- Applying data governance, security and privacy principles, including GDPR requirements.

- Working with cloud data platforms such as AWS, Microsoft Azure, Google Cloud, BigQuery or Snowflake.

-Fluent in English and French.

Why join us ?

At VATES, you will find a flexible work environment, a supportive and approachable team, and a role that makes a real impact on a daily basis.

Location:

Our offices are based in Grenoble or Paris, but we operate on a fully remote model to provide greater flexibility and daily work comfort.

You are free to work 100% remotely or come on-site occasionally, depending on your preferences.

Benefits:

-Health insurance coverage funded at 50% by the company

-Benefits provided by the Works Council (employee discounts, cinema tickets, etc.)

-Employee savings plan (PEE)

-Profit-sharing scheme

-Annual bonus

-100% remote work

As part of our diversity and inclusion policy, this position is open to all candidates, regardless of gender.

This position is suitable for someone who enjoys understanding how a business works and turning that understanding into reliable data models.

We are looking for someone with:

-A Bachelor’s or Master’s degree in Data Analytics, Computer Science, Computer Engineering, Statistics, Mathematics

-Severals years (5-7) of experience in data analysis.

-Fluent in English and French.

Experience with some of the following would be appreciated:

- SaaS or subscription business models.

- Sales, CRM or Revenue Operations data.

- Finance and billing data.

- Data quality frameworks.

- APIs and application integration.

- Software engineering practices such as version control, automated testing and CI/CD.