Top Data Analyst Jobs in Hungary

Build scalable data architectures, dashboards, ETL strategies, and AI-enabled analytical solutions using Salesforce data platforms. Analyze patterns, create forecasts and predictive models, and deliver actionable insights for business decision-making. Collaborate cross-functionally to align analytics solutions with business goals and architecture standards. The role requires experience with Salesforce data, Tableau or Power BI, statistics, Python, structured and unstructured data, predictive modeling, AI technologies, and Salesforce Service Cloud.

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.

Analyze FMCG sales, pricing, promotions, customer, product, margin, market share, and competitor data to support revenue growth management. Develop pricing and price elasticity models, identify commercial opportunities, create visualizations and actionable insights, and translate analytical needs into product requirements, user stories, and business rules. Collaborate with stakeholders, product managers, data engineers, developers, and commercial teams to build scalable digital analytics solutions.

Develops and maintains forecasting models for clinical site payments, integrating Medidata Payments data and supporting financial reporting. Analyzes plan-versus-actual performance, budget variances, and forecast risks; prepares client-ready reports and reconciliations. Partners with Revenue Recognition, Clinical Operations, Project Analysis, and planning teams to support audits, change orders, study closeouts, compliance, and sponsor reporting requirements.

Monitors medical device complaint data flowing from Salesforce into Snowflake, maintains Power BI dashboards, performs SQL trend analyses, and presents signal detection findings to QA, regulatory, and operations teams. Ensures data quality, traceability, documentation, and alignment with post-market surveillance, complaint-handling, audit, and regulatory requirements.

Analyze and improve fraud signals and user segmentation for Puzzleplay’s rewards platform. Investigate suspicious and manually reviewed users, monitor segment effectiveness, identify gaps in detection, and recommend verification tools. Collaborate with product and data teams to turn analysis into operational fraud controls across different markets as fraud patterns evolve.

Design finance data models, requirements, mappings, standards, lineage, and scalable data solutions. Support migration to Snowflake, data quality and governance, regulatory reporting, automation, and AI-enabled analytics. Collaborate with Finance, Data, and Technology stakeholders to translate business needs into technical specifications and improve data accessibility, reliability, and usability.

Leads Salesforce data stewardship across requirements, migration, cleansing, governance, quality monitoring, issue remediation, and cutover readiness. Defines data standards, field rules, validation criteria, and documentation while coordinating business and technical teams. Supports integrations, reporting impacts, compliance, audit activities, user training, and data quality improvement. Requires Salesforce Data Cloud certification, strong data management experience, and approximately 10–20% global travel.

Leads Salesforce enterprise data governance, hygiene, quality, privacy, compliance, and Data Cloud operating standards. Establishes data rules, stewardship models, identity resolution practices, remediation processes, metrics, and executive reporting. Partners with security, legal, architecture, integration, MDM, ERP, and AI teams to ensure trusted, compliant data. Requires Salesforce Data Cloud certification, a bachelor’s degree, and 7+ years of relevant experience. Includes approximately 10–20% global travel.

Leads international analytics and platform support across more than 100 countries. Maintains Power BI reports and dashboards, administers Salesforce and CSOD, validates and uploads data, supports system releases and user issues, tracks operational actions, and improves data quality. Develops automation using Microsoft Copilot, Power Automate, and Power Apps while partnering with IT and shared services on reporting infrastructure, platform enhancements, stakeholder support, and process improvement.

Supports analytics, reporting infrastructure, business intelligence platforms, and data quality across more than 100 countries. Develops Power BI dashboards and reports, administers Salesforce and Cornerstone LMS accounts, validates and uploads data, performs ad hoc analysis, and supports system releases, UAT, issue tracking, and end users. The role also develops automation solutions using Copilot, Power Automate, and Power Apps, while coordinating stakeholders, action items, and operational improvements.

Own end-to-end analytics for subscription products and web funnels, including KPI definition, dashboards, funnel and cohort analysis, payment performance, user behavior, experimentation, and anomaly monitoring. Build reliable SQL data models and maintain event taxonomies and tracking. Partner cross-functionally with Product, Marketing, Engineering, Finance, and BI to improve conversion, retention, revenue, and LTV. Mentor analysts and communicate actionable recommendations to stakeholders.

Leads Salesforce enterprise data governance, quality, compliance, and stewardship across Salesforce Data Cloud and core clouds. Establishes privacy, retention, masking, consent, security, deduplication, enrichment, and data quality standards. Oversees Data Cloud streams, identity resolution, profile unification, segmentation, activation controls, data lineage, and Salesforce-to-ERP synchronization. Develops quality metrics and executive reporting, coordinates cross-functional remediation, supports migrations and cleansing, and improves master data alignment. Requires Salesforce Data Cloud certification, strong data governance and MDM expertise, SQL knowledge, and 7+ years of relevant experience.

Leads Salesforce data stewardship across requirements, migration, cleansing, validation, governance, and quality remediation. Maintains data dictionaries and standards, resolves data issues, validates integrations and transformation rules, supports compliance and audit activities, and ensures data consistency across business groups. Partners with business and technical teams to improve data quality, reporting integrity, security, and user adoption. The role requires Salesforce Data Cloud expertise, analytical skills, governance discipline, and approximately 10–20% global travel.

Own GTM and sales analytics across pipeline performance, forecasting, funnel conversion, win/loss analysis, lead and account scoring, territory planning, quota modeling, and capacity planning. Partner with RevOps, Sales, Product, Finance, and Analytics Engineering to improve metric definitions, Salesforce and product data models, dashboards, and decision-making. Translate complex analysis into clear recommendations for GTM leadership.

Own end-to-end product and marketing analytics for subscription products and web funnels. Define KPIs, build trusted dashboards and reusable SQL data models, analyze funnels, cohorts, retention, LTV, churn, and user behavior, and identify optimization opportunities. Maintain event tracking and taxonomy, monitor anomalies, communicate insights to stakeholders, and mentor junior and mid-level analysts. Collaborate cross-functionally with Product, Marketing, Data Engineering, and BI teams to support experimentation and data-driven decisions.

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.

The Senior Data Analyst will provide product, operations, and business analytics; analyze internal, market, and customer data; translate findings into actionable insights; improve product features; define data models; ensure data quality; and build dashboards and analytical models using Snowflake, Looker, Amplitude, and related tools. The role also involves A/B testing, causal inference, stakeholder communication, and collaboration with data engineers.

As an Optimization Lead, you will maximize campaign performance using data-driven insights and collaborate with various teams to implement optimization strategies.

Ensures the quality, completeness, and accuracy of mortgage valuation data across reporting and valuation processes. Responsibilities include data validation, reconciliations, anomaly investigation, root cause analysis, output verification, stakeholder coordination, testing, documentation, audit controls, and process improvement. The role supports implementation of a new mortgage valuation platform and bridges Finance, Risk, Technology, data providers, and business teams.

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.

Lead analysis and visualization of complex datasets to support pricing, product, customer, market, supply chain, inventory, and operational decisions. Develop executive reporting, scalable data models, self-service analytics, and AI-enabled data quality capabilities. Investigate discrepancies, improve processes, define data requirements, and collaborate with global cross-functional teams. Translate complex insights for technical and non-technical audiences while mentoring junior analysts and driving continuous improvement.

Leads complex data acquisition, analysis, visualization, and executive reporting across pricing, products, supply chain, inventory, and business performance. Builds scalable data models, improves self-service analytics and data quality, evaluates AI-enabled analytics capabilities, and translates transactional data into actionable recommendations. Partners with global cross-functional stakeholders, defines analytical requirements, supports process improvements, communicates insights clearly, and mentors junior analysts.

Analyzes clinical trial scientific and operational data to support risk-based quality management and centralized monitoring. Develops surveillance plans, configures KRIs and statistical analyses, reviews data for trends and outliers, documents findings, escalates quality issues, and collaborates with global project teams. Presents findings in internal and external meetings, supports regulatory inspections, coordinates follow-up actions, and completes central monitoring reports.