Python állások XIII. kerületben (adatrögzítő)

• 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 configuration

• 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

• Definition and improvement of metrics representing product performance and operations efficiency
• Data collection from multiple sources ensuring accuracy and completeness
• Data cleaning, organization, and transformation into usable formats for analysis

• Search, collect, consolidate, and validate financial and non-financial data across departments and systems
• Design, build, maintain, and automate dashboards and underlying data pipelines to provide timely, accurate insights to stakeholders

• Co-design and implement QA workflows using statistical diagnostics, validation rules, and anomaly detection techniques
• Apply AI/machine learning tools to identify inconsistencies, missing values, or suspicious patterns in large-scale asset datasets

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Solution design and delivery
• Design and configuration of data labeling and processing pipelines using Python-based tools

• 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

Performing tasks related to the position....

• Definition and improvement of metrics reflecting product performance, service quality, and operational efficiency
• Analysis of client behavior and service processes to identify trends, bottlenecks, inefficiencies, and drivers of performance

• Development and refinement of core sports betting models for predicting match outcomes
• Building and maintenance of player statistics models analyzing player performance
• Design and implementation of risk management models to optimize exposure

• Dashboard development for sustainability data visualization
• Data integration from various sources for comprehensive reports
• Client reporting collaboration for customized visual analytics
• Data analysis to identify trends and support sustainability initiatives

• Building complex financial analysis utilizing Microsoft Excel, Python, Alteryx, KNIME, Power BI & Tableau
• Taking part in significant international transaction projects
• Collecting, researching and analyzing data related to the client’s business operations

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

• 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

• Analysis of webshop and digital campaign performance across multiple brands and channels
• Building and maintaining campaign benchmarking databases using historical performance data
• Development of forecasting methodologies and performance estimates for future campaigns

• Data ingestion processes from various sources into the Data Lake
• Design, development, and optimization of complex data pipelines for reliable data flow
• Build, development, and maintenance of frameworks facilitating the construction of data pipelines

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain
• Analysing and resolving blockers and issues with ETL pipelines and data discrepancies

• Measuring performance of multi-channel patient recruitment campaigns
• Optimizing multi-channel patient recruitment campaigns
• Forecasting performance of multi-channel patient recruitment campaigns
• Translating recruitment data into actionable insights
• Accelerating enrollment
• Reducing site burden

• Development, testing, and maintenance of data pipelines to extract, transform, and load (ETL) data from various sources
• Writing high-quality, maintainable Python code
• Participation in code reviews
• Participation in technical discussions for tool selection and architectural decisions

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems