Senior Data Analyst

WHAT DO SENIOR DATA ANALYSTS DO @ METRUM (part of Resultance Group)?

Our Senior Data Analysts are analytical problem-solvers with a strong business mindset and a passion for turning data into impact.

As specialists inData Reporting & Visualization, they turn complex data into meaningful insights, enabling organizations to make data-driven decisions and optimize their performance. With expertise indata analysis and data visualization tools (like Power BI), they design and implement cutting-edge reporting solutions that enhance productivity and streamline decision-making.

At Metrum, the technical arm of Resultance Group, you will work at the heart of data-driven transformation, supporting organizations in optimizing performance through high-quality analytics, reporting, and insights.

And more precisely, you will help organizations leverage data to drive operational excellence and smarter decision-making.

WHAT WILL YOU DO ?

Data & Analytics

• Lead complex data analyses to answer strategic business questions
• Perform advanced exploratory data analysis (EDA) to identify trends, risks, and opportunities
• Define and monitor KPIs aligned with business objectives
• Design, build, and maintain executive-level dashboards and reports
• Translate analytical findings into clear, actionable recommendations for stakeholders

Advanced Analytics & Modeling

• Build and maintain analytical models (forecasting, segmentation, cohort analysis)
• Conduct A/B testing and experimentation analysis
• Define analytical frameworks and methodologies for client use cases
• Review and validate analytical work produced by junior analysts
• Ensure robustness, consistency, and interpretability of analyses
• Design, build, and maintain reliable data pipelines (batch and streaming)
• Develop and optimize complex SQL transformations on large-scale data platforms
• Implement data models optimized for analytics and performance
• Ensure data quality, lineage, and consistency across the data stack
• Collaborate closely with platform and infrastructure teams

Tools, Platforms & Analytics Stack

• Work hands-on with modern data stacks (Synapse, Databricks, Snowflake, etc.)
• Build and maintain analytics infrastructure supporting self-service BI
• Implement orchestration and transformation frameworks
• Contribute to CI/CD practices for analytics and data pipelines
• Evaluate and recommend tools and architectural improvements

Business Intelligence & Data Visualization

• Design and maintain advanced dashboards for operational and executive audiences
• Define visualization standards and data storytelling best practices
• Ensure dashboards are powered by scalable, well-modeled data sources
• Enable self-service analytics for business teams
• Monitor usage and continuously improve analytics products

Client & Stakeholder Engagement

• Act as the primary analytics point of contact for clients
• Understand business needs and translate them into analytical requirements
• Present insights and recommendations to senior stakeholders and executives
• Support decision-making through data storytelling and visualization
• Contribute to scoping, planning, and delivery of analytics engagements
• Contribute to define analytics best practices and standards within the organization
• Review deliverables to ensure quality, clarity, and business relevance
• Contribute to internal knowledge sharing and training initiatives
• Promote a data-driven culture within client organizations

Transversal & Strategic Contributions

• Contribute to analytics strategy and roadmap definition for clients
• Participate in internal R&D or innovation initiatives
• Drive continuous improvement of analytics processes and workflows
• Represent the analytics practice in internal or external communities

OK, AND HOW CAN YOU GET THERE?

• You hold aMaster’s degreein Data Science, Business Analytics, Economics, Engineering, Computer Science, or a related field
• You are fluent inFrench and English(any other languages such as German are strong assets)
• You have2-3 years' experiencein:
• SQL and relational databases
• SQL Server / SQL Server Management Studio
• SSIS, SSAS, SSRS
• Power BI or equivalent
• T-SQL, PL/SQL, or equivalent language
• Use of cloud environments (Azure, AWS, GCP)
• Code versioning with Git
• Setting up collaborative notebooks (Databricks, Jupyter)
• Introduction to MLOps best practices (testing, simple monitoring)
• Translating complex data