Python programmer állások, munkák adminisztráció, asszisztens, irodai munka területen

• Translation of business requirements into KPIs, metrics and visualizations
• Building and maintaining semantic and analytical data models on top of the data warehouse
• Writing and optimizing SQL queries, views and calculated measures for reporting use cases

Design, develop, and maintain interactive Power BI dashboards and reports to support spend analysis, supplier performance, contract lifecycle management, and procurement KPIs...

• Development of dashboards and reporting solutions
• Support of data integration and operational initiatives
• Analytical investigations and identification of trends, risks and opportunities
• Collaboration with operational teams and stakeholders
• Provision of data analysis, reporting and performance insight

• Aktuárius gyakornokként nem-élet aktuáriusi, riportálási feladatokban vehetsz részt
• Pénzügyi gyakornokként tapasztalatot szerezhetsz a klasszikus és biztosításspecifikus számvitel és adózás, továbbá a biztosító treasury területén

• Assisting in integrating data from various sources into centralized data platforms
• Ensuring the quality and availability of data across data pipelines and storage systems
• Supporting the implementation of data models and data warehouse solutions
• Monitoring data workflows and assisting in troubleshooting

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Design and configuration of data labeling and processing pipelines
• Combination of multiple data labeling components into automated workflows

FLEXIBILITY- The times of punishments for coming 5 minutes late are gone. We have flexible home office policy as well!...

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Leading and developing the three-person QC function including workload planning, prioritization and performance management
• Defining daily and weekly QC priorities based on project deadlines, production capacity and quality risk

• Configuration of the P&P platform end to end across frontend and backend
• Tuning and optimization of forecast and attribution models to match client data and business logic
• Writing custom business logic in SQL, Python, or Go for non-standard configurations

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Improvement of operational efficiency through process optimization, automation, and adoption of new technologies
• Understanding of the company's data warehouse and alignment of data flows with reporting requirements

• Elemzés globális szolgáltatásminőségi adatokon
• Nem megfelelőségek, helyesbítő és megelőző intézkedések, ügyfél visszajelzések és audit eredmények elemzése
• Minták, ok-okozati csoportok, ismétlődő problémák és kockázatok azonosítása
• Elemzések átalakítása világos következtetésekké és ajánlásokká

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Experience in different data science topics including machine learning, LLM, deep learning
• Independent delivery of data science projects with e2e product-oriented mindset
• Direct engagement with clients to understand business objectives and translate into technical requirements

• Designing, developing, and evaluating machine learning models on complex telecom and retail data
• Transforming high-volume datasets into production-ready solutions such as churn prediction models and point-of-sale fraud models

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD

• Lead the design and implementation of scalable data pipelines and Lakehouse architectures
• Act as the design authority
• Solve the hardest technical challenges including optimizing high-load streaming pipelines, debugging complex Spark jobs, and designing generic frameworks

• Supporting business and marketing decisions with data-driven solutions
• Developing predictive models such as churn scoring to drive retention offers and product propensity scoring
• Translating business needs into actionable ML and AI solutions across marketing, customer care, and network operations