Sql állások, munkák adatrögzítő kategóriában

• Üzleti igények elemzése
• Folyamatok tervezése az érintett területek bevonásával
• Üzleti követelmény specifikációk készítése
• Üzleti területek támogatása
• Kapcsolattartás az IT és üzleti területek között
• Üzleti tesztek koordinálása
• Teszt tervek készítése
• Projektekben való részvétel

Performing tasks related to the position....

• 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

• 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 engineering builds against
• Own the measurement standard including canonical definitions, naming, field ownership, versioned change control across every business unit

• 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

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• 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

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

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

• 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

• Building and maintaining SQL queries and reports that track bookings, pipeline coverage, and conversion
• Monitoring CRM data quality to resolve issues at the source
• Analyzing pipeline trends and supporting the weekly forecasting review cadence with clean, accurate data

• 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

• Business and system analysis throughout the full feature lifecycle
• Analysis and mapping of processes across the trading stack including accounts, instruments, liquidity and execution, custody, settlement, and reconciliation

• 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 internal databases, external APIs, and third-party platforms
• Client reporting collaboration with sustainability team
• Data analysis to identify trends, patterns, and insights

• Power BI riportok és dashboardok fejlesztése és karbantartása
• Üzleti igények elemzése és technikai megvalósítása
• Adatmodellek és adatvizualizációk kialakítása
• PL/SQL alapú lekérdezések, tárolt eljárások és adattranszformációk fejlesztése
• Adatminőség és riportok validálása

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• 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