Senior Data Analyst
Job description
About the role
Enterprise customer data guides commercial choices. This role analyzes that data to direct account management and commercial strategy. You will translate complex data sets into clear narratives that help the commercial team understand account health and opportunity. The work involves turning raw information into decisions that influence how the company manages its key accounts. You will work closely with business stakeholders to ensure the insights generated are relevant and actionable. This position requires a mix of statistics, coding, and communication to bridge the gap between data and commercial execution. A strong portfolio of past analyses will be central to your candidacy. Nearly every modern company runs on data teams, and this role is critical within that context.
Key facts
What you'll do
Investigate enterprise customer data to uncover patterns that inform account management priorities.
Develop queries and dashboards that provide the commercial team with a clear view of customer behavior and lifecycle stages.
Collaborate with commercial partners to define the metrics that matter most for tracking account success.
Analyze trends across customer segments to identify risks and expansion opportunities.
Support the evaluation of commercial initiatives by measuring outcomes against established benchmarks.
Translate technical findings into concise narratives that help the team prioritize their outreach and strategic focus.
Work with data infrastructure to ensure the accuracy and reliability of the sources used for analysis.
Challenge assumptions by validating hypotheses through rigorous examination of historical and current data.
Participate in cross-functional discussions to align on goals and the interpretation of key performance indicators.
Contribute to a data-driven culture where decisions are consistently backed by evidence and clear visualization.
Provide ongoing monitoring of account health indicators to support proactive commercial interventions.
Assist in building the analytical foundation that enables the commercial team to forecast and plan effectively.
Document methodologies and logic so that analyses remain transparent and reproducible over time.
Support ad hoc requests that help the team respond quickly to emerging opportunities or issues in the market.
Requirements
The posting states a bachelor's degree requirement. A degree is necessary for this role. Foundational knowledge for the analysis work is ensured by this requirement.
The role requires eligibility for visa sponsorship as stated.
Standard team collaboration expectations apply to the Amsterdam-based position.
You must possess the right to work in the Netherlands as sponsorship is available for the correct candidate.
A background in a quantitative field is expected to handle the analytical demands of the position.
Strong proficiency in SQL is required to extract and manipulate data from enterprise databases.
Experience with dashboarding tools is necessary to communicate insights visually to non-technical stakeholders.
Solid understanding of statistical concepts is required to interpret data correctly and avoid misleading conclusions.
Excellent communication skills are mandatory to present complex findings to commercial audiences clearly.
The ability to work independently and manage multiple analytical requests simultaneously is essential.
Practical notes
Typical interview steps
Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study. Candidates may be asked to design a metric, interpret an experiment, or build a small model. Some companies give a take-home analysis. Expect questions about past projects and the business impact of your work. Interviewers often evaluate how you communicate uncertainty and business impact, not only the math. Bringing a clean write-up of a past analysis to the interview is well received.
Good to know
Questions to ask
Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.
Career growth
Data careers grow toward senior analyst, staff data scientist, or data engineering lead. Many professionals specialize in machine learning, analytics, or infrastructure. Cross-functional work with product and engineering teams becomes more important at senior levels. The field changes quickly, so continuous learning is part of the job. Professionals who can translate numbers into decisions tend to advance fastest.
About the company
Adyen is a financial technology platform providing end-to-end payments infrastructure, data analytics, and financial products. Founded by Pieter van der Does and Arnout Schuijff in 2006, Adyen went public on Euronext Amsterdam in 2018. Its clients include Meta, Uber, Spotify, and Microsoft.