Top Data Analyst Jobs in Poland

Manage vendor and purchasing master data across procure-to-pay functions. Analyze large datasets, maintain data quality, resolve escalated issues, identify root causes, recommend corrective actions, and support compliant global processes. Create reports, dashboards, and KPI visibility while collaborating with purchasing, accounts payable, leadership, and other stakeholders. Contribute to process improvements, change management, workflow management, and operational excellence initiatives.

Manage reference market data: set up and maintain securities, validate vendor feeds, respond to client inquiries, perform quality control, run market data analyses, and support process improvements while collaborating with internal and external stakeholders.

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.

Leads independent data analysis projects, translating business challenges into analytical problems and actionable recommendations. The role analyzes complex datasets, validates insights, develops visualizations and dashboards, and presents findings to business stakeholders. It also facilitates discovery workshops, defines KPIs, documents data flows and business processes, and serves as a liaison between business teams and data engineering to ensure accurate, strategically valuable reporting.

Perform commercial data analysis and reporting across Western Europe, including distributor sales and price claims processing. Maintain the Commercial Excellence database, develop Excel-based tools, support Finance and commercial teams, provide local analytical support, and contribute to process-improvement projects. The role requires accurate data management, cross-functional collaboration, analytical recommendations, and communication in English and Polish.

Process and validate user access requests and recertifications for confidential-data applications, maintain audit-ready evidence, manage high-volume workloads, escalate and resolve exceptions, support entitlement cleanup and tooling/automation improvements, and compile evidence for audits while partnering with stakeholders and Technology.

Build and maintain Tableau reports and dashboards, administer Tableau Server, and translate complex datasets into clear insights for non-technical stakeholders. Work with SQL and ETL pipelines to integrate and optimize large-scale data, troubleshoot performance, and support analytics team deliverables. Communicate findings, collaborate with peers, and continuously learn.

Lead data analytics and management to validate regulatory reporting data across regions. Collaborate with finance, regulatory, technology and program teams to scope needs, improve data quality, drive consumption readiness, support regulatory changes, and deliver process and operating model improvements.

Analyze large datasets to generate business insights across payments, tax-free, currency conversion, and hospitality. Build and maintain advanced Power BI dashboards, automate reporting, manage end-to-end analytics projects, gather requirements, and translate business needs into technical solutions. Collaborate with data engineers on ETL pipelines, data models, governance, and scalable BI solutions. Mentor team members and promote analytics best practices and innovation.

Collaborate with stakeholders to translate business requirements into analyses, analyze large datasets to identify trends, build and maintain dashboards and visualizations (Power BI), validate data quality, support analytics projects (cohort, funnel, retention), and improve reporting processes to drive data-driven decisions.

Collects and analyzes consumer, market, and campaign data; develops statistical models, dashboards, and customer presentations; and collaborates with teams to explain insights and support business decisions. The role requires analytical problem-solving, data pipeline and dataset experience, strong Excel and PowerPoint skills, and professional English communication. Recent graduates and candidates with 1–3 years of analytics or marketing analytics experience are encouraged to apply.

Develop and support analytical systems for operational decision-making, identify KPIs with business process owners, analyze data lifecycles, define data warehouse and ETL requirements, validate data engineering results, build dashboards, and present insights to customers. The role requires at least one year of data or BI analyst experience, strong SQL and data visualization skills, analytical communication abilities, and fluency in Russian and English.

Lead setup and lifecycle of Master Data Data Products, manage a small external team, design and implement data product pipelines in Snowflake, coordinate governance and data quality (Ataccama), own requests/incidents, and collaborate with stakeholders, infrastructure, and developers to deliver production-ready, source-agnostic data products.

Manages supplier master data creation, maintenance, updates, and issue resolution across Oracle, Navision, and Microsoft Dynamics. Supports Accounts Payable and Procurement, advises employees on supplier and customer creation procedures, analyzes AP information, performs adjustments, maintains request forms, identifies data improvements, and assists with audits. Requires accuracy, problem-solving, communication, English fluency, and familiarity with ERP and office systems.

Partner with product teams to use behavioral and business data for discovery, prioritization, experimentation, and delivery. Analyze customer journeys, funnels, conversion, adoption, engagement, retention, and segments; build dashboards and BI reports; improve Amplitude usage, instrumentation, and metric definitions; support A/B testing; and communicate actionable insights to technical and non-technical stakeholders.

Own end-to-end product analytics for the Pro team: build production-grade pipelines and dbt models, define north-star metrics, design A/B tests and causal inference frameworks, create dashboards and metric frameworks, embed AI tooling, and translate insights into product recommendations for leadership.

Design, develop, and maintain Power BI reports and Power Platform solutions (Power Apps, Power Automate). Clean, transform, and analyze data using SQL, Excel, and Python. Collaborate with stakeholders to gather requirements, automate workflows, and communicate insights to technical and non-technical audiences.

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.

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.

Develop data-driven insights and strategic recommendations to detect and prevent fraud across channels. Analyze multi-channel fraud trends, evaluate tools and AI use cases, measure control effectiveness, and translate findings into executive-ready, cost‑benefit informed actions to reduce fraud while balancing customer experience and operational efficiency.

Collect, clean, and analyze procurement data to drive sourcing strategies, supplier performance, and process improvements. Build and maintain Power BI dashboards and reports, lead data cleansing and classification, support sourcing events (RFx), execute MRP processes in SAP APO/ECC, prepare forecasts, and collaborate with cross-regional procurement and category teams to align POs and resolve supply issues.

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.

The Commercial AI Solutions Analyst will collaborate with teams to implement AI initiatives and ensure data quality for business insights. Responsibilities include data validation, user acceptance testing, and promoting AI literacy within sales.

Analyze sales and commission data, translate business needs into technical requirements, design and test calculation logic and system configurations, validate calculations using SQL and Excel/VBA, support implementations, training, and process optimization for global clients, and occasionally travel for business.

Support marketing and commercial teams by delivering analytics and insights, building dashboards and self-service reports, automating ETL and data workflows with SQL and Python, contributing to data products (e.g., contact DataMart), and supporting campaign setup, audience selection, and lead processing.