Top Data Analyst Jobs in Germany

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 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.

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.

Partner with founders and cross-functional teams to analyze financial and operational data, build executive dashboards, create P&L and margin analyses, forecast and model unit economics, identify cost leaks, reconcile transactions, and present recommendations to improve profitability, cash flow, and business performance.

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.

Lead and grow the RevOrg analytics team, own revenue KPIs, reporting, forecasting, attribution, and data governance. Align GTM functions on unified metrics, drive data quality and scalable analytics frameworks, and deliver executive-ready insights to support predictable SaaS revenue growth.

Lead end-to-end revenue analytics and forecasting, build lifecycle dashboards, develop multi-touch attribution, measure marketing and sales productivity, and drive data quality and governance across CRM and GTM systems.

Trace and document client, account, fund, holding, and position records across legacy source systems. Work with German-speaking system owners to understand data structures, identifiers, documentation, and record definitions. Specify extraction, transformation, and loading rules; coordinate with mainframe platform teams; define downstream data requirements; and reconcile migrated records to prove completeness and accuracy. The role requires fluent German and English, securities-services domain knowledge, hands-on data profiling and reconciliation experience, mainframe familiarity, and on-site work in Düsseldorf.

Partner with Marketing, Sales, Finance, Product and other teams to turn business questions into actionable analysis. Own end-to-end analytics: build datasets and dashboards (dbt, LookML), maintain metric definitions and caveats, use and curate agent tooling for trustworthy answers, and contribute small data platform and pipeline improvements.

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.

Manage business analysis, agile facilitation, metadata, and data delivery operations for Springer Nature’s DDS platform. Translate stakeholder needs into requirements, analyze data flows and dependencies, facilitate Kanban ceremonies, and coordinate initiatives. Maintain ONIX, XML, and MARC feeds; support libraries and external partners; configure delivery processes; validate data quality; and contribute to migrations, automation, cloud improvements, and TDM feeds.

Lead cross-functional analytics to drive commercial, marketing, and financial decisions. Monitor performance, model impact, build dashboards and automate reporting, ensure data integrity, and translate ambiguous business questions into decision-ready insights that shape profitability and resource allocation.

Lead technical analyses to detect and prevent ad fraud at scale. Build and optimize SQL/Python data pipelines, apply anomaly detection methods, design experiments, automate reusable analytics frameworks, and communicate findings to technical and non-technical stakeholders to drive business decisions.

Partner with Sales and RevOps to analyze the revenue funnel, design territory/quota models, build forecasts and dashboards, run experiments and causal analyses, and deliver actionable insights to improve sales performance and drive revenue.

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.

Lead experimentation and A/B testing analyses using SQL and Python on large-scale data (100TB). Design experiments, compute sample sizes, apply variance reduction, detect anomalies, automate reporting and dashboards, and collaborate with product, engineering, and growth teams to translate results into business decisions.

Perform geospatial and data analysis to support operational planning and strategic assessments across the Africa AOR. Integrate, clean, and visualize structured and unstructured datasets; produce maps, reports, and briefings for senior leaders in classified and unclassified environments.

Lead design and development of scalable data models and Power BI reporting using Databricks, DBT and SQL. Partner with product and business stakeholders to translate requirements, drive analytics delivery, and support cloud migration to modern Azure-based analytics. Mentor colleagues, champion analytics best practices, and contribute to AI-enabled self-service capabilities.

Join Oliver Wyman's Data & Analytics team to design and implement analytic solutions and prototypes for clients across industries. Work on NLP, ML, and GenAI projects, build models (e.g., PD, loss models) in Python/R, validate AI chatbots, and translate complex analytics for client decision-making while collaborating with global teams.

Support Central Europe Data & Analytics by building consistent KPIs and Power BI reports, analysing leasing, occupancy and financial performance, gathering and modelling data from lakes/warehouses, driving AI tool adoption, supporting systems requirements/testing, and partnering with operations and asset teams to improve NOI, reporting and operational execution.

Support billing and payments by extracting and analyzing financial data with SQL and spreadsheets, reconcile transactions across platforms, resolve discrepancies with external partners, and build reports and dashboards translating technical findings into business insights.

As a Senior Data Analyst in Operations, you'll analyze data to provide insights that drive business decisions, enhance performance, and support strategic initiatives.