Top Data Analyst Jobs in Berlin

Build and improve Enfuce’s people-data foundation by cleaning, structuring, connecting, and governing data across systems. Develop trusted BI reporting, analyze engagement, retention, workforce efficiency, and headcount trends, and provide actionable recommendations. Define success measures and evaluate people initiatives. Partner with the People, Data & AI, Finance, and People Product teams to support AI-powered automations and products using reliable data.

Own fraud-focused user segmentation for Puzzleplay. Analyze and refine fraud signals, investigate flagged users, monitor segment effectiveness, improve manual review processes, and recommend verification tools. Partner with product and data teams to develop operational fraud controls and adapt detection methods as fraud patterns evolve across markets.

Analyze large-scale marketing and user acquisition data to measure campaign performance, build automated Tableau dashboards, evaluate A/B tests, and identify growth opportunities. The role develops marketing measurement strategies, integrates attribution data from providers such as AppsFlyer and Kochava, partners with Data Engineering, and communicates actionable recommendations to technical and non-technical stakeholders.

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.

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 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.

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.

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.

Leads research and advisory work for CIOs on data, analytics, and AI strategy, governance, operating models, architecture, value realization, and emerging technologies. Develops thought leadership, market analysis, presentations, and actionable client guidance; evaluates agentic and composite AI, modern data platforms, AI-ready data, organizational maturity, and capability-building needs. Represents Gartner at client meetings and conferences, supports sales, mentors colleagues, and shapes research agendas.

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.

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.

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.

Analyze open-ended product and commercial questions to guide decisions across Product, Sales, Customer Success, and leadership. Investigate account growth, retention, expansion, product adoption, funnel performance, experimentation, and pricing. Build dbt models and Looker views to support analysis, communicate clear recommendations, and independently drive the analytical agenda using SQL, Python, BI tools, and AI tools.

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.

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.

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.

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.

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.

The Senior Data Analyst will own reporting topics, support audits, design dashboards, lead BI initiatives, and drive effective decision-making in a fast-growing fintech company.