Top Data Analyst Jobs in Berlin

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.

Analyze product data across mobile games to guide experimentation and product decisions. Responsibilities include designing A/B tests, defining success metrics, performing segmentation, cohort, funnel, and predictive analyses, ensuring reliable event tracking, building dashboards, and communicating insights. The role partners closely with product managers, designers, and engineers while using AI tools and automation to improve analytical efficiency.

Analyze Agentic AI, CRM workflows, and hyperautomation initiatives to measure operational efficiency, ROI, quality, and business impact. The role involves advanced SQL, Python or R analysis, process mining, experimentation, BI dashboard development, data modeling, and stakeholder communication. The analyst partners with product, engineering, and operations teams to identify workflow bottlenecks, support process redesign, improve self-service analytics, and establish reliable monitoring for operational KPIs and SLAs.

Analyze financial metrics and performance, develop KPIs, support forecasting, budgeting, variance analysis, and cost optimization, and build financial dashboards. Partner with Finance, product, engineering, and business teams to deliver actionable insights, improve data infrastructure, enable self-service reporting, and strengthen financial data literacy.

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

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.

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.

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.

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.

Analyze product and business performance for the Customer Identity segment, establishing measurable goals, evaluating experiments, building dashboards, and delivering actionable insights. The role partners with product, engineering, design, and research teams; supports tracking and self-service data platforms; improves organizational data literacy; and contributes to product discovery, experimentation, forecasting, and business strategy.

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.

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.

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.

Transform cloud, AI, SaaS, and on‑prem billing data into forecasts, dashboards, and optimisation recommendations. Build cost models, KPIs, automate pipelines and reporting, validate forecasting tools, drive tagging and allocation strategies, and advise clients through workshops and consulting engagements.

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.

Analyze and process tumor-derived NGS datasets (RNA‑Seq, WES, WGS, single‑cell), develop and apply bioinformatics pipelines, interpret cancer genomics results, collaborate with multidisciplinary teams, and contribute to diagnostic solution development.

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 multilingual data quality by analyzing and cleaning text data, developing parsers, evaluating text classifiers, translating taxonomies (Skills, Titles, Occupations), and partnering with Linguistics and Engineering to deliver high-quality global data.

Drive product and business insights through exploratory analysis, metric governance, dashboards, and A/B testing. Partner with Product, Business, Data Platform, and Engineering teams to define success metrics, guide roadmap decisions, improve experimentation, prepare reliable analytical data, and promote data self-sufficiency across the organization.