Top Data Analyst Jobs in Germany

Leads ad hoc and exploratory analyses for medical and business questions across a global Medical Insights organization. Prepares and validates datasets, translates ambiguous stakeholder needs into decision-ready findings, and maintains analytical documentation. Tests new data sources, methods, and AI-enabled approaches through proof-of-concept analyses to guide platform investments and roadmap decisions. Partners with business and product stakeholders while supporting compliant, reproducible use of regulated data.

Build end-to-end compliance analytics and data infrastructure for KYC/KYB funnels, remediation campaigns, and financial exposure. Model and transform data with dbt and Omni, create self-service dashboards for product, ops, risk and compliance, and measure campaign impact to drive operational decisions.

Analyze manufacturing and production data to identify performance drivers, bottlenecks, anomalies, and optimization opportunities. Build dashboards, reports, data pipelines, features, and quality metrics while collaborating with customers, AI and backend engineers, Product, and Customer Success. Translate operational insights into improvements for customer outcomes and the company’s AI analytics platform. Occasional travel to manufacturing plants is required.

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.

The Data Analyst will leverage data to provide insights, automate reporting, improve customer/vendor experiences, and help reduce returns costs at Quince.

Analyze player behavior, engagement, progression, segmentation, cohorts, and A/B tests using SQL and analytical data models. Build reliable, documented datasets, support reporting and visualization, and translate findings into actionable insights for product and game teams. Collaborate cross-functionally to influence roadmap decisions and improve analytical workflows and standards.

Leads analytics within a cross-functional product team by designing scalable data models with dbt, SQL, Databricks, and Microsoft Fabric. Builds Power BI dashboards and semantic models, translates business needs into technical solutions, influences prioritization, modernizes cloud analytics products, and advances self-service and AI-assisted analytics. Mentors analysts, promotes best practices, and collaborates closely with technical and business stakeholders.

Apply data analytics, machine learning, and AI to production activities; identify digitalization use cases; deploy AI solutions on OpenShift; develop business reports; and replace Excel-based tools with automated solutions using Palantir Foundry, OpenShift AI, and TIBCO Spotfire.

Lead marketing analytics and M&A data integration initiatives. Harmonize KPIs, attribution, reporting, and data landscapes; build scalable marketing data models and ELT pipelines; create dashboards; analyze advertising and mobile measurement platforms; deliver executive insights; and lead cross-functional analytics projects involving multiple business units.

Owns business and performance analysis for B2B2C products, partners, and markets. Analyzes large datasets, builds commercial and operational reports, identifies trends and opportunities, and translates findings into recommendations for senior stakeholders. Supports pricing analysis, partner reviews, benchmarking, and business cases while collaborating with Product, Sales, Finance, and Operations. Ensures reporting accuracy and consistent interpretation across dashboards and reports.

Transforms graphene photonics characterization data into insights for device design, process development, and manufacturing. Owns analysis software and scalable data infrastructure, develops methods for evolving experiments, ensures data integrity and traceability, extracts device parameters, performs statistical and yield analyses, correlates measurements with process parameters, and integrates outputs with fab MES systems for real-time process feedback. Requires strong Python development, device physics knowledge, model fitting, visualization, and laboratory or fab instrument experience.

Provides independent technical data analyst support for the M2i raw materials intelligence platform. Responsibilities include designing data models and analytical datasets, integrating and validating data sources, developing and optimizing Power BI reports and Microsoft Fabric components, improving refresh performance, implementing access management and usage monitoring, performing quality assurance, documenting technical solutions, and preparing platform enhancements for future releases.

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.

Collect, clean, and analyze large datasets to measure digital campaign performance, identify trends and causal impact, run experiments, build predictive models, and create visualizations and dashboards to inform business decisions.

Lead design and delivery of scalable analytics solutions using dbt, SQL, Databricks and Microsoft Fabric. Build Power BI dashboards and semantic models, collaborate with product and business stakeholders, modernise cloud analytics, mentor analysts, and promote analytics best practices including AI-assisted capabilities.

Owns the transformation of raw digital marketing data into business-ready insights. Develops ETL/ELT pipelines, SQL-based BigQuery transformations, marketing data marts, and advanced Tableau and Looker Studio dashboards. Standardizes KPI definitions, ensures consistency across GA4, Adobe Analytics, and reporting outputs, documents governance practices, optimizes BI performance, and enables self-service reporting through user training and stakeholder collaboration.

The Staff Data Analyst in Marketing Analytics develops statistical models, performs quantitative analysis, proposes marketing strategies, and mentors others while collaborating with marketing and data engineering teams.

The Data Analyst will own analytics projects, develop customer-facing data products, conduct quantitative analysis, and drive decision-making through data insights.

As a Data Analyst, analyze user behavior and product performance to create reports and dashboards, collaborating with teams for data-driven insights.

Own B2C marketing KPIs and analyze acquisition funnels, attribution, conversion, trials, and churn. Build reporting frameworks, self-serve data products, and AI-powered insights; improve tracking, measurement, compliance, and advertising-platform data activation. Partner cross-functionally with Marketing, Product, and Data teams to translate complex analyses into actionable growth, budget, channel, and acquisition recommendations.

Analyze and govern commercial data across Finance, Pricing, and Revenue Operations. Build SQL and dbt data pipelines, consumption models, audit-ready data products, and Looker Studio dashboards. Reconcile and validate complex datasets, translate business logic into reliable metrics, and communicate actionable insights to technical and non-technical stakeholders. The role requires close collaboration with globally distributed teams in a hybrid Berlin office environment.

Analyze, validate, and interpret business, customer, and product data to generate actionable insights. Build and maintain Power BI dashboards, reports, and KPI solutions; monitor data pipelines; support data quality and governance; and maintain data catalogs and KPI definitions. Collaborate with stakeholders through Jira workflows, enable self-service analytics, and communicate findings clearly. The role requires SQL, PySpark or Python, Excel, Power BI, statistical knowledge, German and English proficiency, and openness to AI-driven analytics.

Perform deep operational data analysis, build queries and dashboards, automate ETL and data processes, develop monitoring tools, present insights and recommendations to management, and collaborate with squads using SQL, Python/R and visualization tools.

Lead operational analyses and present data-driven recommendations. Query data lakes with SQL, perform deep-dive analysis in Python/R, automate ETL and monitoring, build dashboards (Metabase), and communicate insights to influence business decisions.

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.