Requirements

Expected technologies

Tableau

QV

Power BI

SQL

Python

R

Our requirements

• Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field
• Proven experience in data visualization tools, specifically with Tableau, QV and Power BI.
• Strong analytical skills with a solid understanding of data analysis and interpretation.
• Strong skills in SQL and scripting
• Familiarity with ETL processes and tools
• Expertise in data modeling and design
• Experience in designing and building scalable data pipelines
• Familiarity with data visualization best practices and design principles.
• Experience with other data visualization tools or programming languages (e.g., Python, R) is a plus.
• Preferred:
• Relevant certifications (e.g., GCP Certified, AWS Certified, Azure Certified)
• Strong analytical and communication skills
• Ability to work collaboratively in a team environment
• High level of accuracy and attention to detail

Your responsibilities

• Communication and Collaboration:
• Show an awareness of the need to translate technical concepts into non-technical language
• Understand what communication is required with internal and external stakeholders
• Provide training and support to end-users on dashboard functionalities and data interpretation.
• Work closely with data engineering and IT teams to optimize data sources for visualization.
• Data Analysis and Data Visualization:
• Design, develop, and maintain interactive dashboards and reports using data visualization tools (Tableau, Power BI, …) that cater to various business needs.
• Collaborate with cross-functional teams to gather requirements and translate them into effective visual solutions.
• Analyze and interpret large datasets to identify trends, insights, and opportunities for improvement.
• Implement best practices in data visualization to enhance clarity, usability, and engagement.
• Data Development Process:
• Design, build and test data products based on feeds from multiple systems, using a range of different storage technologies, access methods or both
• Create repeatable and reusable products
• Data Innovation:
• Show an awareness of opportunities for innovation with new tools and uses of data
• Data Modeling:
• Explain the concepts and principles of data modeling
• Produce, maintain and update relevant data models for an organization's specific needs
• Reverse-engineer data models from a live system
• Testing:
• Ensure data quality and integrity through data cleansing and validation processes.
• Understand the role of testing and how it works
• Focus on first project will be the responsibility to replicate or reconnect the current infrastructure (ETLs, Local data warehouses and data visualization tools) used by the countries in EMEA region. The target scenario will be a global infrastructure cloud-based data platforms (AWS, Snowflake, Tableau..) combining information in two different levels:
• Global pipelines and global data models
• Local pipelines to enrich the global data models covering the necessities of the countries in terms of business.