Top Data Analyst Jobs in the Netherlands

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.

Own the strategy, governance, compliance, budgeting, and value realization of the firm’s external market data portfolio. Map datasets to trading, research, and technology use cases; forecast consumption and costs; manage vendor negotiations and entitlements; evaluate data quality and coverage; support pilots and integrations; and collaborate with Legal, Compliance, Engineering, Finance, Trading, and Research.

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.

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.

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.

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.

Conduct exploratory and business data analysis, build and maintain dashboards, translate stakeholder needs into data work, support experiments and investigations, and document queries and standards. Present actionable findings clearly to nontechnical colleagues while ensuring data accuracy and reliability. The role includes working with SQL and data visualization, with opportunities to use Metabase, dbt, Python, or R.

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.

Own supply-side analytics: define and monitor partner KPIs, build self-serve dashboards and LLM-powered tools, run experiments and A/B tests, create business cases for commercial decisions, support provider integrations, and raise analytics standards across the team.

Lead end-to-end analytics projects for hardware infrastructure automation: design data models and pipelines, build dashboards, analyse large-scale telemetry, quantify automation impact, and present actionable recommendations to engineering stakeholders. Ensure data quality, documentation, and mentor colleagues to improve team standards.

Owner of analytics and data pipelines: deliver proactive analysis, build and maintain dbt models, ensure pipeline health, troubleshoot data quality, and present clear insights to leadership to drive growth, finance, and product decisions.

Analyze large-scale user and product data, design and evaluate A/B tests, define and validate product and business metrics, build dashboards and reports, and partner with engineers, data scientists, product, and customers to translate insights into product improvements.