Top Data Analyst Jobs in Budapest

This role involves analyzing employee engagement, culture, and DE&I metrics to provide actionable insights for HR leaders and stakeholders, using BI tools to create reports and dashboards, while ensuring adherence to data privacy standards.

Manage operational customer and product master data in SAP and related systems (creation, maintenance, pricing, contracts). Ensure data quality, SOX/GDP compliance, perform audits and bona fide checks, coordinate with cross-functional teams, and support continuous improvement to prevent supply issues.

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.

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.

Support global procurement by delivering analytics, dashboards, and should-cost models; track savings and value delivery; enable data-driven sourcing strategies and business cases; maintain reporting frameworks; support digital procurement tools and partner with Procurement, Finance, and Supply Chain to drive performance and continuous improvement.

Process vendor invoices and usage data, resolve discrepancies in supply, pipeline, and utility invoices, generate client reports, coordinate with suppliers/utilities, support software testing, and analyze complex energy contracts to ensure data accuracy.

Design, build and maintain interactive BI dashboards, perform exploratory analysis on commodity markets, ensure data quality and pipelines, produce KPIs and insight reports, and support stakeholders with self-service analytics and training.

Develop and maintain the front-end of a risk and analytics platform using React (or similar), implement front-office features, design backend API endpoints, build data visualizations (Plotly, ApexChart, D3.js), code/test/debug/monitor functionality, and collaborate with cross-functional teams on technical requirements.

The Salesforce Data Analyst designs data architectures, analyzes patterns, develops predictive models, and leverages Salesforce data for decision-making.

As a Data Business Analyst, you'll design data models, develop semantic capabilities, manage projects, and assist business partners in leveraging data techniques within the Non-Financial Risk domain.

Embedded with a product squad as the PMs' dedicated data partner, lead deep cross-product analyses focused on activation and adoption, design and evaluate experiments, improve instrumentation and event taxonomies, surface retention and cohort insights, and translate rigorous statistical analyses into actionable product recommendations.

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.

The Finance Systems Data Analyst supports the Finance organization by ensuring data accuracy across SAP and Snowflake, optimizes data flows, automates reporting, and enhances financial decision-making.

The Finance Systems Data Analyst ensures accuracy and accessibility of financial data across SAP and Snowflake, optimizing data flows and reporting.

Perform hands-on data analysis and support EMEA commercial and sales teams. Build and maintain Power BI dashboards and reports, optimize SQL queries, support data modeling and ELT processes, manage Power Automate workflows, ensure reporting accuracy, handle ad-hoc requests, and collaborate with senior analysts while contributing to process improvements and learning.

Analyze billing performance, build and maintain data pipelines, run A/B tests, apply statistical forecasting and scenario modeling, collaborate with cross-functional teams, and provide recommendations to reduce risk, disputes, churn, and operational inefficiencies.

The Senior Data Analyst will conduct data analyses, support stakeholders with insights, design dashboards, and improve data quality to enhance user experiences and inform business strategies.

The Lead Billing Data Analyst will own data strategy for subscription billing, enhance performance metrics, guide a team of analysts, and ensure effective reporting and analytics are conducted.

The Senior Data Analyst will manage subscription billing analytics, optimize queries in ClickHouse, and create dashboards for stakeholders. Responsibilities include data pipeline maintenance and anomaly investigation.

As a Senior Data Analyst, you will analyze data to generate insights, create reports and dashboards, and collaborate with product teams, driving strategic decisions based on data.

Own Growth analytics end-to-end: build and maintain production data pipelines and dbt models, define north-star metrics and dashboards, design and run A/B experiments using causal inference, embed LLM/GenAI tooling, and translate insights into strategic recommendations for leadership.