Python Dashboard Developer

What You'll Do

• Stakeholder Collaboration: Work with project managers, resource managers, IT teams, and other stakeholders to gather requirements, define project scope, and ensure alignment with business objectives. • Data Analysis: Collect, analyze, and interpret datasets from R&D projects to uncover trends, key performance indicators, risks, and opportunities.
• Translate complex data into meaningful business insights through reliable, high‑quality visualizations and clear analytical storytelling. • Dashboarding & Reporting: Design, develop, and maintain powerful and trustworthy dashboards and automated reports using Python.
• Ensure that visualizations clearly communicate insights and support impactful decision‑making.
• Gather user feedback and iterate to continuously improve usability and impact. • Data Engineering Support: Collaborate with data engineers to improve data pipelines, data quality, and data models used for reporting and analytical products. • Automation & DevOps: Build analytics solutions with a DevOps mindset—ensure reproducibility, automation, and quality by leveraging CI/CD pipelines, version control, and modern development practices.
• What you bring[FP1.1] You can describe yourself as follows: Education & Experience • Education: A master’s degree[RE2.1][FP2.2][RE2.3] in Business Intelligence, Data Engineering, Data Science, Software Engineering, Computer Science, or a related field. • Experience: 5+ years of experience as a BI developer, preferably within a complex IT or R&D environment.
• Technical Skills • Coding: Strong proficiency in Python and SQL, including experience working with data processing libraries and frameworks.[RE3.1][MN3.2][RE3.3] Hands on experience with Shiny, Plotly and other python visualization packages is a big plus. • Visualization: Experience building dashboards and reports, and a passion for data visualization and user‑centric design. • Automation: A strong interest in automation, cloud technologies, Infrastructure as Code (preferably using CDK), DevOps practices, and CI/CD pipelines (preferably using Gitlab).[FP4.1] Professional Attributes • Strategic Problem-Solving: Comfortable owning technical challenges and designing long-term, scalable solutions. • Customer & Stakeholder Focus: Strong communicator who can translate technical concepts into business value and collaborate effectively across data science, architecture, and wider R&D. • Team Mindset: A natural collaborator who contributes to an open, supportive working culture • Agile & Scrum: Experienced working in Agile environments, actively participating in sprints, stand-ups, and iterative delivery cycles to ensure continuous improvement and timely value delivery.
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