Data Visualization Specialist (Part-Time)

Role overview

This part-time opportunity is being handled by a partner company, which will review applications and manage the next stages of the hiring process. The role is based in Germany and is focused on turning complex data into clear insights that support product direction and business decisions.

The position sits at the crossroads of analytics, product strategy, and end-user impact within a globally distributed, mission-driven team. You will help build dashboards and analytical tools that give leaders a better view of user behavior, product performance, engagement patterns, and areas where improvements can drive better outcomes across multiple markets.

Success in this role depends on both analytical strength and the ability to communicate findings in a simple, compelling way. The work directly supports decisions that shape digital services used in diverse contexts and regions.

Key responsibilities

• Create clear, user-friendly dashboards and visual reports that highlight important metrics and trends, using tools such as Google Data Studio.
• Check data quality and reliability by finding, investigating, and fixing inconsistencies or technical problems in datasets and reporting flows.
• Work with product leaders to design executive dashboards that inform roadmap choices and commercial planning.
• Analyze performance data across regions to uncover patterns, trends, and actionable recommendations.
• Carry out funnel and churn analysis to understand user journeys, spot friction points, and suggest ways to improve retention and engagement.
• Turn technical analysis into easy-to-follow, narrative-style insights for leadership, partners, and other stakeholders.
• Help define product metrics and support a consistent measurement approach across teams.

Requirements

• Three to five years of experience in data analysis, data visualization, or a similar analytical function.
• Strong SQL skills for working with large datasets.
• Practical experience using dashboarding platforms such as Google Data Studio or comparable tools.
• Advanced Excel ability for analysis, reporting, and data modeling.
• Good troubleshooting skills, including the ability to diagnose data issues and explain technical topics clearly.
• Comfort working independently while also collaborating effectively in remote, cross-functional, global teams.
• Exposure to data warehouse tools such as BigQuery, Snowflake, or Redshift is considered an advantage.
• A degree in Computer Science, Data Science, Statistics, or a related discipline is preferred.
• Genuine interest in using data to improve digital services and user outcomes in emerging or varied markets.

Benefits

• Flexible part-time arrangement at 50–60% effort.
• Fully remote work setup within a global team.
• Chance to contribute to meaningful, large-scale digital services across multiple countries.
• Collaboration with international product and data teams in a mission-driven environment.
• Exposure to strategic decision-making that influences product growth and user experience.
• Compensation that is competitive and aligned with experience and scope of responsibility.

Application and privacy information

This hiring process uses an AI-assisted matching workflow to help screen applications quickly, consistently, and fairly against the role’s main requirements. The shortlist is shared with the employer partner, while interviews, assessments, and final decisions are handled internally by their team.

By applying, you consent to the processing of your personal data for candidate evaluation and sharing relevant information with the hiring employer, in line with applicable data protection laws including GDPR. You may exercise your rights to access, correct, delete, or object to processing at any time.

AI tools may also be used to support parts of the recruitment workflow, such as resume review, application analysis, response assessment, and detection of inconsistencies or verification signals. These tools assist recruiters but do not replace human judgment, and final hiring decisions are made by people.