Analytics Engineer

• Design and build Microsoft Fabric Semantic Models (Power BI datasets) on top of Gold‑layer Lakehouse and Warehouse data products
• Define DAX measures, hierarchies, relationships, and semantic model structures
• Develop production Power BI dashboards for Trader P&L, Global Position, VaR, and Financial Consolidation
• Work directly with trading, risk, and finance stakeholders to translate reporting requirements into semantic model design
• Optimize DirectQuery and Import mode performance for complex financial and trading datasets
• Define naming conventions, metric hierarchies, and semantic governance standards for the Fabric workspace
• Collaborate with Data Engineers to ensure Gold‑layer outputs are analytics‑ready
• Support self‑service analytics enablement for client analysts
• Contribute to UAT, report validation, and business sign‑off on accuracy and performance

Analytics Engineer, Power BI Specialist

• Take ownership of central analytical topics and data-driven questions
• Perform ad-hoc analyses for various business units
• Analyze complex relationships and prepare findings
• Own reporting and analysis workflows
• Translate technically complex requirements into data models and analyses
• Support monthly reporting and market analyses
• Standardize recurring analyses and develop sustainable solutions

Data Analyst, Analytics Engineer

• Development, enhancement and maintenance of Informatica workflows – ETL/ELT processes, data processing and data integration
• Analysis, optimization and stabilization of existing batch and scheduling pipelines in the mainframe environment – TWS
• Support for data migrations, modernization projects and archiving/retention initiatives
• Conducting error analysis, performance tuning and end-to-end monitoring to ensure stable data processes
• Close communication and collaboration with business units, infrastructure teams and operations
• Creation, maintenance and continuous updating of technical documentation

Informatica ETL Developer

• Own and operate our marketing measurement stack, including funnel measurement (MMM, MTA, incrementality), AppsFlyer, and Funnel.io, ensuring data quality, model integrity, and actionable outputs across all paid channels
• Build and maintain scalable dbt data models and Tableau dashboards that enable self-service reporting on UA (user acquisition) health metrics (cohort ROAS, CPL trends, payback periods, LTV curves)
• Develop predictive LTV models for hybrid monetization (IAP + ad revenue) and own SKAdNetwork conversion value schemas for iOS
• Translate measurement outputs into concrete budget recommendations and channel-mix decisions for senior stakeholders
• Own the full marketing data-collection layer, from tracking specs and tag management (GTM, server-side) to first-party event design and data contracts with Product and Engineering, ensuring every relevant user action is captured correctly and flows reliably into the measurement stack
• Design and oversee A/B tests for store pages (ASO/CPP), creative concepts, and bid strategies to optimize the full conversion funnel
• Conduct market segmentation and customer-journey analysis to uncover acquisition and retention opportunities
• Collaborate with Data Engineering to ensure reliable data pipelines between AppsFlyer, ad networks, and our BI stack

Senior Analytics Engineer – Marketing

• Development, enhancement and maintenance of Informatica workflows - ETL/ELT processes, data processing and data integration
• Analysis, optimization and stabilization of existing batch and scheduling pipelines in the mainframe environment - TWS
• Support for data migrations, modernization projects and archiving/retention initiatives
• Execution of error analyses, performance optimizations and end-to-end monitoring to ensure stable data processes
• Close communication and collaboration with business units, infrastructure teams and operations
• Creation, maintenance and ongoing updating of technical documentation

• Ownership & objectives: Act as the driving force behind Rosental's data-driven growth
• Create transparency across all business areas
• Translate numbers into clear decisions
• Build the Data & Insights nervous system
• Develop dashboards and visualizations (Power BI, Looker, or Tableau)
• Deliver business insights and actionable recommendations in close collaboration with Brand, D2C and Retail leads
• Establish automated reporting and insights processes
• Support forecasting and performance management with consistent, relevant data

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