Sql developer állások XI. kerületben (adatrögzítő)

• Főbb feladatok
• Termékfejlesztési kérdések lefordítása mérhető és elemezhető kutatási kérdésekké.
• A kérdés megválaszolásához szükséges adatok és adatforrások meghatározása.
• Külső, megvásárolt fogyasztói, piaci, retail, termékbevezetési, trend- és egyéb adatbázisok elemzése.

• 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

Performing tasks related to the position....

• Design of behavioural telemetry including event and entity-state schemas and instrumentation specification
• Ownership of measurement standard including canonical definitions, naming, field ownership, and versioned change control

• 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

• Design the behavioural telemetry event and entity-state schemas and write the instrumentation specification
• Own the measurement standard including canonical definitions, naming, field ownership, versioned change control

• 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

• 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

• Build and maintain SQL queries and reports that track bookings, pipeline coverage, and conversion
• Monitor CRM data quality to resolve issues at the source
• Analyze pipeline trends and support the weekly forecasting review cadence with clean, accurate data

• 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 with Power BI to visualize sustainability data and metrics
• Data integration from various sources including internal databases, external APIs, and third-party platforms
• Client reporting with customized visual analytics solutions

• Analysis of global service quality data including non-conformance costs, corrective and preventive actions, customer satisfaction, NPS, and audit findings
• Transformation of analysis into clear conclusions and prioritized recommendations for regions, central functions, and management

• 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

• Improvement of repetitive processes using AI
• Organization and checking of data used by the Operations team
• Connecting everyday tools to reduce manual work
• Experimentation with AI tools, chatbots and workflows
• Troubleshooting and solving smaller operational tasks

• Technikai menedzsment és fejlesztés a csapat felhőalapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint
• Üzleti logika adatmegoldássá történő átalakítása multinacionális csapatban

• 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

• Design and develop normalized and denormalized data models to support reporting and data integration needs
• Apply dimensional modelling techniques to create efficient, scalable, and business-oriented data models
• Develop and maintain data transformations and models using SQL and dbt

• Primary adviser on sales force effectiveness topics
• Segmentation and targeting cycles ownership
• Customer universe and route-to-market updates
• Sales incentive plan design and governance
• Sales incentive plan target setting, rules, settlement and performance monitoring

• Lead client discovery and solutioning
• Own the information design layer
• Design and develop executive and tactical BI solutions
• Elevate client reporting maturity
• Leverage AI tools in daily workflow
• Bridge analysis and communication
• Drive semantic model design and development