Top Data Analyst Jobs in Krakow

Build sustainability dashboards, data models, templates, and reporting frameworks using Power BI, Excel, Snowflake, and Streamlit. Track ESG metrics including Scope 1–3 emissions, circularity, waste, water, energy, and materials. Establish data validation, governance, transformation, and audit-ready processes while partnering with IT and cross-functional teams. Conduct trend analysis, scenario modeling, and ad hoc analytics to support sustainability strategy and decision-making.

Analyzes and transforms data into actionable business insights. Builds Power BI dashboards, automates workflows with Power Automate, develops Power Apps applications, and uses SQL, Excel, and Python for data processing and analysis. Collaborates with stakeholders to define requirements, communicates findings to nontechnical audiences, and supports process improvement and digital transformation initiatives.

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.

Produce and maintain automated Looker dashboards and semantic models, translate supply-chain telemetry into insights, optimise BigQuery SQL, clean and model WMS/ERP data, run statistical analyses, and embed AI-assisted workflows to improve inbound stock flows and warehouse throughput.

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.

Analyze website traffic, conversion funnels, and digital campaign performance. Build automated dashboards in Looker Studio or Tableau. Write complex SQL to extract and blend data, manage GA4 tracking and BigQuery exports, generate insights tying web data to business outcomes, and support A/B test analysis for CRO.

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.

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.

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.

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 Data Analyst will assist with visa/VOE case history, data entry for new hires, and resolve employee queries using HRMS while ensuring quality and compliance.

Analyze marketing data to evaluate spend, build attribution and reporting, and deliver actionable insights. Create and maintain dashboards, ensure data integrity, collaborate with marketing and data engineering teams, and improve analytical methods to support data-driven decisions.

Partner with Product teams to analyze user journeys, run A/B tests, build dashboards, extract insights using SQL, Tableau and Amplitude, and collaborate with Data Platform engineers to drive data-informed product decisions.

Analyze mobile games data to track performance, design and execute A/B tests, report on user engagement, and recommend optimizations.

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.

The Data Governance & Quality Analyst ensures data accuracy and consistency, supports decision-making, and drives data quality improvements.

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.

Analyze user behavior on websites and apps, focusing on KPIs and data visualization. Build dashboards, run A/B tests, and communicate findings to stakeholders.

Lead product analytics across multiple products: own event tracking, funnel analysis, A/B testing framework, AI/LLM-driven insights, dashboards, and reporting. Ensure data quality, define KPIs, run experiments, automate monitoring, and collaborate with Product, Engineering, Marketing, and leadership to drive data-driven decisions.