Top Data Analyst Jobs in Cologne

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.

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.

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.

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 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.

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.

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.

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.

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.

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.

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