Finance & Commercial Data Analyst II: Insights & Dashboards

Adyen; Amsterdam; On-site; EUR 60,000 - 80,000; Full time

Job summary

Adyen seeks a Data Analyst II in Finance and Commercial to transform complex data into clear insights, building scalable analytics from dashboards to data pipelines and collaborating with data engineers and cross-functional partners across the business.

You will develop revenue operations data pipelines with SQL, Python, LookML, and Looker, ensure data quality, automate recurring reports, and translate findings into actionable recommendations for global commercial teams.

Qualifications

• 2-4 years of experience in Data Analytics.
• Proficiency in Python and SQL for data analysis and processing.
• Good communication and collaboration skills, with the ability to work effectively within a global, multicultural team.
• Data Wrangling expertise: cleaning, transforming, and organizing large datasets, handling missing data, detecting outliers, and ensuring data integrity.
• Good analytical skills: adept at extracting meaningful insights from complex datasets and translating them into actionable recommendations.
• Flexibility for occasional business travel to support global collaboration and projects

Responsibilities

• Develop and maintain revenue operations data pipelines and ETL improvements.
• Build and maintain LookML models and Looker dashboards to deliver accurate, timely insights for commercial stakeholders.
• Ensure data quality and governance by cleaning, transforming, and documenting datasets to ensure accuracy.
• Automate recurring reporting processes (e.g., Quarterly Business Reviews, pipeline reporting).
• Analyze datasets and translate findings into actionable insights for the commercial teams.

Skills

Python

SQL

Data analytics

Communication

Collaboration

Data wrangling

LookML

Looker

Tools

LookML

Looker

PySpark

Airflow

Git

Job description

Adyen seeks a Data Analyst II in Finance and Commercial to transform complex data into clear insights, building scalable analytics from dashboards to data pipelines and collaborating with data engineers and cross-functional partners across the business.

You will develop revenue operations data pipelines with SQL, Python, LookML, and Looker, ensure data quality, automate recurring reports, and translate findings into actionable recommendations for global commercial teams.