Top Data Analyst Jobs in Warsaw

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.

Design, build, and maintain Power BI dashboards and Microsoft Fabric data pipelines. Integrate Dynamics 365 data, ensure data quality and governance, deliver executive insights, forecasting, and strategic analysis. Partner with sales, operations, and finance leaders to translate requirements, promote self-service analytics, and document KPIs and reporting logic.

Lead business-facing data analysis to assess data models, identify duplicates and inconsistencies across sources, and recommend practical data quality and governance improvements. Run discovery sessions, present findings to stakeholders, produce documentation, roadmaps, and support prioritisation of data improvement initiatives to enable better business decisions.

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.

Lead the billing analytics function: build and maintain billing data pipelines and dashboards, analyze payments/renewals/refunds/disputes, run experiments and forecasting, reduce churn and disputes, and manage/mentor a team of analysts while partnering with Billing, Support, Finance, Product, and Marketing.

Analyze billing and support performance, build and maintain data pipelines, apply statistical forecasting and A/B testing, collaborate cross-functionally, document analyses, and provide recommendations to reduce financial risk, disputes, churn, and operational inefficiencies.

Lead data governance and quality workstreams for client transitions: gather requirements, define data structures, perform data quality assessments, document standards and processes, and communicate findings to account teams and clients.

Lead establishment and execution of a sustainable data concerns and adjustment operating model within Risk. Track data quality initiatives, perform analysis, design process improvements, document requirements, manage stakeholders, prepare reporting, and support risk/issue remediation and governance reporting.

Lead delivery of end-to-end data and analytics solutions: build dimensional models, develop Power BI dashboards, perform exploratory analysis, design Azure-based data pipelines, capture client requirements, run scenario modelling, test and assure solutions, prepare client communications and lead project teams.

Lead data and analytics projects: design dimensional models, build Power BI dashboards, run exploratory analysis, capture client requirements, develop end-to-end data pipelines on Azure, test and assure solutions, support client decision-making, and contribute to business generation and people development.

Lead data governance and MDM strategy for a global client: establish policies, build stewardship programs, create data dictionaries, partner with IT/BI and stakeholders, reduce risk, and advise on governance best practices to improve data-driven decisions.

Identify, assess, and mitigate risks in clinical trial data by performing risk assessments, monitoring data quality, collaborating with cross-functional teams, using statistical analysis and visualization, and preparing risk management documentation for regulatory submissions and audits.

Leads research and client advisory on emerging AI data security and AI ecosystem data management trends. Develops research reports, presentations, briefings, and tailored recommendations for technology executives and product leaders. Analyzes technologies, vendors, markets, and competitive landscapes; builds expert networks; delivers client inquiries and speaking engagements; and collaborates with analysts and service teams to ensure high-quality research. The role requires deep cybersecurity and AI data expertise, strong writing and presentation skills, executive presence, and up to 25% travel.

Lead end-to-end business operations workstreams for RDT Data & AI, translating requirements into implementation plans, performing deep-dive analyses, and improving processes (compliance, quality, dashboards, vendor management). Act as a trusted advisor to cross-functional stakeholders to drive operational excellence and organizational effectiveness.

Assess and mitigate risks to clinical trial data by conducting risk assessments, monitoring data quality, collaborating with cross-functional teams to implement risk management plans, performing statistical analysis and visualizations, and preparing documentation for regulatory submissions and audits.

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.

Maintain and validate global customer master data across systems (Salesforce, Jira), perform deduplication and hierarchy management, conduct compliance checks (embargo/VAT screening), monitor CMD dashboards, support cross-functional teams to resolve data anomalies, and drive data integrity projects and process improvements.

Partner with Marketing to analyze acquisition, budget efficiency, and growth drivers. Build dashboards, run proactive analyses, automate recurring work, collaborate with cross-functional teams, and present clear, actionable recommendations to stakeholders to inform marketing strategy and budget allocation.

Work on supply-side product and business analytics for direct accommodation contracts. Build and automate reporting, analyze internal/external data, design prioritization/segmentation and predictive algorithms, and partner with product, commercial, and international teams to improve supplier performance and guide strategic decisions.

Work with France-based analysts to ensure commercial data accuracy, provide operational backup, build and maintain Power BI dashboards, monitor sell-out vs BI data, perform data quality reviews and root cause analysis, improve reporting and support data-driven decision making for Sales and local management.

Partner with cross-functional teams to turn data into insights, build and maintain impactful dashboards, run analyses using SQL and visualization tools, support A/B testing and retention/churn projects, and collaborate with data engineers to ensure data quality and availability.

Perform deep-dive analyses of player behavior and in-game economy, provide strategic recommendations to product and monetization teams, build interactive Tableau dashboards to monitor KPIs, collaborate with data engineering and design, translate complex data into clear narratives, identify optimization opportunities across the player journey, and mentor junior analysts.

As a Senior Data Analyst, you will analyze data, create reports, manage data pipelines, and provide insights to influence product decisions. You will collaborate with various teams and perform A/B testing.

The Business System Analyst collects and analyzes requirements for IT solutions, verifies business needs, and advises on optimal solutions, while cooperating with internal and external partners.

Lead retention and marketing analytics: build lifecycle and segmentation frameworks, design and analyze A/B tests, drive personalization and KPI dashboards, automate retention reporting, and partner with Marketing, CRM, Product, and Data Engineering to turn insights into action.