JetBrains - Business Intelligence Analyst (m/w/d)
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Requirements
• Proven years of experience in a BI, data analysis, or similar analytical role. • Strong SQL skills and experience with Python, R, or another relevant programming language. • Experience with BI and visualization tools such as Tableau, Power BI, Qlik, DataLens, or similar. • Understanding of data warehousing concepts, relational databases, and data processing workflows. • Experience working with structured datasets and building reliable reporting solutions. • Strong analytical thinking, attention to detail, and curiosity about data. • Ability to communicate clearly with both technical and non-technical stakeholders. • Professional working proficiency in English. • Experience working with Sales, Marketing, or other go-to-market domains, especially in B2B environments. • Hands-on experience building ETL pipelines and preparing datasets for analytics. • Experience working with dbt or similar data transformation tools. • Familiarity with data governance and data quality practices. • #LI-HYBRID#LI-REMOTE#LI-JP1 • We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
Responsibilities
• Partner with Sales stakeholders to define analytical requirements, metrics, and KPIs, and identify opportunities for improvement. • Develop and maintain dashboards, reports, and visualizations that provide timely and actionable insights. • Analyze revenue streams and contribute to forecasting using statistical, heuristic, or machine learning approaches. • Perform exploratory and ad hoc analyses to support decision-making across Sales and related teams. • Collaborate with data engineers to design and implement data marts, reporting layers, and ETL pipelines; contribute to our dbt-based analytics infrastructure. • Support Sales Development and Lead Generation teams by analyzing experiments and campaign performance. • Monitor data quality across reporting assets and work with data owners to resolve issues. • Document metrics, dashboards, and data sources, and help stakeholders effectively use analytics tools. • Promote self-service analytics by enabling teams to access and interpret data independently.
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