Top Data Analyst Jobs in Warsaw

Analyze, transform, validate, and investigate large datasets using SQL, Python, and PySpark. Develop ETL processes, resolve data quality issues, document data mappings and transformation rules, and support regulatory and management reporting. Collaborate with data engineers, business analysts, and stakeholders on corporate banking and financial services data, including ESG and regulatory reporting.

Analyzes enterprise data across PostgreSQL, Salesforce, Splunk, and integrated systems. Writes complex SQL queries, investigates logs and data discrepancies, performs reconciliation and validation, identifies root causes, and recommends improvements. Collaborates with technical and business stakeholders to translate requirements into actionable insights, document findings, resolve cross-system issues, and improve data quality and operational efficiency in a financial services environment.

Own and support daily and monthly liquidity risk reporting, including LCR, ALMM, NSFR, stress reporting, and regulatory submissions to global regulators. Analyze large financial datasets, reconcile products, investigate variances, correct data issues, and improve reporting processes using Alteryx, Tableau, and Excel. Collaborate with global stakeholders and support AI-enabled reporting infrastructure while reducing operational risk.

Analyze payments data, integrate complex data sources, maintain performance reports, monitor KPIs, and identify opportunities to optimize payment routing and reduce failures and costs. The role collaborates with Payment Operations, Product, Finance, Customer Support, analysts, and engineers to ensure data quality and deliver actionable insights through ad hoc analysis, dashboards, and automated reporting.

Analyze marketing spend, attribution, and performance data to identify growth opportunities and guide channel decisions. Own analytical projects from scoping through impact measurement, using SQL, Tableau, and AI tools to build reliable analyses and visualizations. Partner with marketing leaders across affiliates, influencers, PPC, SEO, and product marketing, while collaborating with the Data Platform team to improve data availability and scalable workflows.

Analyzes and cleans customer and company data, maintains databases and data systems, identifies trends, produces reports, monitors KPIs, and supports business process improvements. The role requires collaboration with management and data professionals, statistical analysis, data quality monitoring, and communicating findings. Preferred experience includes Power BI, SAP or ERP systems, Alteryx, and service organizations.

Analyze B2B commercial data to identify growth opportunities, design experiments, evaluate pricing and credit-limit initiatives, and measure business impact. Apply SQL, Python, statistical analysis, A/B testing, difference-in-differences, causal inference, and forecasting methods. Work independently with commercial and project teams to support pricing, market expansion, and partner analytics decisions.

Analyze hotel supply data to support commercial and Cloud teams, evaluate partner and chain performance, identify inventory gaps and data-quality issues, and improve reporting consistency. The role involves clarifying ambiguous requests, delivering end-to-end analyses, building trusted dashboards or data products, and communicating findings to nontechnical stakeholders. Experience with SQL is required, while dbt, data modeling, and marketplace or platform experience are advantageous.

The Commissions Analyst optimizes financial performance by managing variable compensation processes, resolving inquiries, and overseeing data accuracy in compensation management.

Supports the global data privacy function by maintaining privacy frameworks, DSAR and erasure procedures, personal data inventories, reporting dashboards, policies, and notices. Assists with third-party risk reviews, contract and DPA assessments, privacy incident monitoring, regulatory compliance, and employee awareness training across multiple jurisdictions.

Own A/B testing and analysis for Paper.io 2, using large datasets to uncover player behavior and growth opportunities. Translate insights into game design and product roadmap recommendations, optimize monetization and core KPIs, and build dashboards and reports. Collaborate with designers, product managers, and developers in a fast-paced live-ops environment.

Manages confidential-data access governance, including access requests, recertifications, removals, exceptions, stakeholder support, audit evidence, and data-quality checks. Uses SQL, Alteryx, Snowflake, and Excel for reconciliation and reporting. Partners with technology teams and data owners to resolve issues, maintain procedures, validate automated outputs, and improve controlled workflows while supporting audit readiness and risk management.

Own analytics for Nuitee’s global travel marketplace, analyzing enterprise partners, self-service API adoption, bookings, product performance, and customer behavior. Build and validate dbt models, data pipelines, experimentation capabilities, and analytical products end to end. Partner with senior Product, Engineering, and commercial leaders to establish trusted metrics, resolve reporting inconsistencies, identify growth opportunities, and influence product and business decisions in a fast-moving startup environment.

Design, build, test and support batch and streaming data pipelines and curated datasets on a Lakehouse/AI data platform. Implement data modelling, schema evolution, partitioning and data quality controls. Work with stakeholders to deliver production-ready, well-tested, high-performance data products and support operational monitoring and reconciliation.

Owns end-to-end product and commercial analytics for an AI cloud platform, including metric definition, customer health, capacity forecasting, utilization, pricing, packaging, segmentation, and monetization. Analyzes large-scale customer and usage datasets, builds production-ready data solutions, and delivers recommendations across Product, Engineering, Finance, Sales, and Operations. The role requires strong Python, SQL, statistics, commercial judgment, and familiarity with consumption-based technical products.

Analyze data quality results, identify risks and root causes, and translate findings into business recommendations. Coordinate cross-functional stakeholders, requirements, reporting, governance documentation, and project deliverables. Prepare executive reports and presentations, track dependencies and risks, facilitate decisions, and improve data governance processes. The role operates within an international credit risk model development team and may involve regulated banking, credit risk modeling, BCBS239, and Agile initiatives.

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.

Analyze complex datasets to identify trends, generate actionable business insights, and support decision-making. Build dashboards, reports, and visualizations using Tableau, Power BI, or Looker. Collaborate with product, engineering, operational, clinical, and business teams on reporting requirements, data quality, governance, data models, cloud warehouses, ETL, and statistical analysis. Communicate findings clearly and support scalable analytics processes across client projects.

Collects and analyzes data across finance, operations, sales, marketing, and creative departments. Builds executive dashboards, reports, forecasts, business models, and cost-benefit analyses to support strategic decisions and revenue growth. Translates complex findings into clear presentations for technical and non-technical audiences, identifies optimization opportunities, supports client reporting, and provides recommendations to company leadership in a fully remote advertising-agency environment.

Owns ETL pipelines and production Python scripts for client data deliverables. Responsibilities include cleaning, reconciling, deduplicating, joining, and transforming multi-source data; integrating Meta, TikTok, and other APIs; mentoring junior team members; quality-checking deliverables; and scoping technical work with analytics and strategic intelligence teams.

Investigate and improve fraud signals, user segmentation, and review processes for a player rewards platform. Analyze suspicious activity, monitor segment performance, evaluate verification methods across markets, investigate manually flagged users, and recommend third-party fraud prevention tools. Collaborate with product, data, and gameplay analysts to translate findings into operational fraud controls and revenue-share decisions.

Processes, transforms, validates, and monitors data workflows to ensure accuracy, integrity, quality, and timely client delivery. Investigates data inconsistencies, documents processes, collaborates with cross-functional teams, manages competing priorities, and contributes to workflow optimization and operational efficiency.

Ensures data accuracy, quality, integrity, and timely delivery by cleaning, transforming, validating, and monitoring workflows. Investigates anomalies, resolves data issues, documents processes, supports client and cross-functional requirements, and contributes to operational improvements. Manages multiple workflows, priorities, and deadlines while maintaining clear data standards and documentation.

Lead analytics for subscription products and web funnels, partnering with Product, Marketing, and Data teams to improve conversion, retention, and LTV. Build trusted dashboards, SQL data models, event tracking structures, funnel and cohort analyses, and A/B testing insights. Monitor metrics, identify anomalies, communicate recommendations, and mentor junior and mid-level analysts while maintaining reliable reporting and data foundations.

Leads advanced data analysis, reporting, dashboard, and data-model development to support strategic decisions and operational efficiency. Analyzes complex datasets, identifies trends and opportunities, defines KPIs, ensures data integrity, automates workflows with AI tools, and presents actionable insights to senior leadership. The role also mentors junior analysts, drives process improvements, and maintains documentation.