Top Data Analyst Jobs in the Netherlands

Support data quality initiatives by cleansing, validating, reconciling, and standardising business data across CRM and enterprise systems. Analyse datasets to find trends and issues, prepare data for reporting and automation, document findings, and collaborate with stakeholders to improve data governance and processes.

Analyze marketplace data to identify growth opportunities, define metrics and OKR targets, forecast performance, build dashboards, support strategic decision-making, and automate recurring reporting workflows. The role partners with stakeholders across strategic initiatives and translates complex analysis into actionable business insights.

Work with Product and Insurance teams to define KPIs, analyze A/B tests, build and maintain real-time dashboards, contribute to dbt-based data pipelines, and provide data-driven recommendations to influence product roadmap and outcomes.

As a Data Analyst, you'll advise clients on data management strategies, implement solutions, and enhance data governance and quality. You'll also provide insights for business decisions based on analytical data evaluations.

Own and improve pricing and product master data across more than 100,000 products. Determine gross prices, monitor ERP data quality, identify duplicates and inconsistencies using automation and AI, and lead data improvement projects with Product Owners and IT. Serve as the pricing and product-data expert within purchasing while supporting international business decisions, profitability, inventory management, searchability, and customer experience.

The Digital Data Analyst ensures accurate data tracking, analyzes performance across digital channels, and reports insights to drive marketing decisions.

Manage Salesforce lead distribution, ownership updates, bulk uploads, deduplication, data standardization, and daily CRM data requests for Netherlands and Germany. Produce outbound campaign performance reports, analyze conversion and data quality, identify process gaps, and recommend improvements to targeting, routing, and follow-up. Advise on data purchases and uploads while coordinating with sales, marketing, and analytics stakeholders across markets.

Own measurement for a product area, define metrics and KPIs, design and interpret experiments, analyze customer funnels, conversion, retention, and cohorts across markets, and improve the metric layer and underlying data. Partner with Product and Growth leaders to guide roadmap decisions and ensure data remains reliable for growth, risk, and financial reporting.

The FP&A Data Analyst will enhance financial reporting, automate processes, bridge data across systems, and develop insightful dashboards while collaborating with finance and engineering teams.

Analyze large datasets to identify trends and deliver actionable insights; design and monitor KPIs; build and maintain dashboards and reporting frameworks; conduct ad hoc analyses; ensure data quality and support reporting infrastructure in partnership with product and business teams.

Analyze and improve customer data processes and tools, create logical data models, business glossary and data directory, define and monitor data policies and standards, advise stakeholders on data management and compliance (GDPR, DORA), drive change management and continuous data quality improvements across business units.

Drive adoption and strategic evolution of Rabobank’s Enterprise Data Lineage Platform. The role translates stakeholder needs into platform capabilities, requirements, user stories, training, communication, and adoption strategies. Responsibilities include facilitating workshops, supporting data governance and organisational change, developing business-focused visualisations, analysing adoption metrics, and shaping product roadmaps. Success requires strong consulting, stakeholder management, communication, storytelling, and data governance expertise.

Early-career Data Analyst responsible for designing and owning core metrics and dashboards, analyzing transaction/customer/credit data to inform credit, fraud, AML, portfolio and growth decisions, building data pipelines and automations with SQL and Python, partnering with cross-functional teams, and owning compliance reporting. Emphasis on turning ambiguous problems into reliable analytical systems and applying GenAI/LLMs for practical automation.

Own end-to-end development of business-critical dashboards and reports, analyze data from SQL and NoSQL sources, and deliver executive-ready insights. Partner with Data Engineering on data quality, pipelines, and models; monitor KPIs across programs, funnels, and revenue; identify trends and bottlenecks; mentor junior analysts; and promote self-service reporting across the organization.

Perform data analysis across growth revenue management, marketing, customer lifecycle, CRM, and risk analytics. Use statistical and programming tools to acquire, clean, integrate, analyze, interpret, and visualize data. Develop hypotheses and actionable recommendations, present findings, facilitate workshops, manage executive stakeholders, and mentor team members.

Perform data analysis across revenue management, marketing, CRM, and risk analytics. Use statistical and programming tools to acquire, clean, integrate, analyze, and visualize data; develop hypotheses and actionable recommendations; present findings to stakeholders and executives; facilitate workshops; and mentor team members.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Supports Oliver Wyman’s Data and Analytics consulting team by designing analytical solutions, developing prototypes, applying machine learning and AI techniques, validating models, and assessing their effectiveness. The role involves collaborating with consultants and clients, explaining complex data science concepts clearly, and contributing to projects across financial services, sustainability, retail, transportation, and other industries. International travel and continuous technology development are expected.

Develop analytical solutions for consulting clients across financial services, sustainability, energy, retail, and transportation. Responsibilities include designing and prototyping data science solutions, applying machine learning and advanced analytics, validating models and GenAI applications, and communicating complex findings to clients and colleagues. The role involves collaboration across global teams, continuous learning, and potential international travel.

Collaborate with consultants and clients to design, prototype, validate, and implement data and analytics solutions. Projects may involve NLP, machine learning, GenAI validation, credit risk modeling, decarbonization, promotion optimization, supply chain risk, and customer churn. Explain sophisticated analytical concepts clearly, contribute to client discussions, and develop quantitative problem-solving skills in a collaborative consulting environment.

Develop analytical and machine learning solutions for global consulting clients, including prototypes, predictive models, NLP, GenAI validation, risk analytics, and optimization tools. Collaborate with clients and colleagues to explain sophisticated data science concepts, assess solution effectiveness, and deliver impactful results across industries such as financial services, energy, retail, and transportation.

Lead data extraction, validation, and migration efforts using advanced SQL and Azure data services. Perform data mapping, reconciliation, quality assessments, and root-cause analysis. Collaborate with stakeholders, data engineers, and project teams to translate requirements, support SIT/UAT, optimize SQL scripts, and maintain technical documentation to ensure data integrity and compliance across migration lifecycles.

As a Data Analyst, you will develop data strategies, enhance data governance, implement data quality processes, and provide data-related insights to clients.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

Develop data-as-a-product solutions and Power BI reports, engage stakeholders to gather requirements, build scalable self-service dashboards, ensure data quality and ethical sharing, train users, and support reporting rollouts for supply-chain and sustainability insights.