Python developer állások X. kerületben (adatbázisszakértő)

• ORACLE/PostgreSQL/MariaDB adatbázisok telepítése, konfigurálása, frissítése (legalább egy terület üzemeltetési szintű ismerete)
• Adatbázis kiegészítők telepítése, kezelése,
• Több lábas clusterek építése, üzemeltetése (PATRONI HA / RAC – DATAGUARD / GALERA),

• Maintaining and evolving data structures
• Building new ETL flows and maintaining/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 and build scalable data warehousing and lakehouse solutions
• Operate scalable data infrastructure and lakehouse solutions
• Create and own robust ELT pipelines connecting multiple internal and external data sources
• Design and implement data models aligned with industry best practices

• statisztikai és gépi tanulási modellek fejlesztése, karbantartása és monitorozása
• piackutatások készítése
• adatvezérelt megoldások kidolgozása az értékesítés, kárrendezés, ügyfélkiszolgálás és termékterületek támogatására

• 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

Vizualizáció és döntéstámogatás: Interaktív Dashboardok és riportok készítése, ahol a vezetők valós időben követhetik a cég fő mutatóit, amelyek közvetlenül támogatják a döntéshozatalt. A keletkező nagy mennyiségű adat tisztítása, rendszerezése, értelmes, emészthető és számszerűsíthető...

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Design and enforcement of data architecture standards including Delta Lake / Lakehouse architecture and data modeling

• Understanding underlying data structure of an ERP system (Microsoft Dynamics 365 Finance & Operations)
• Creating technical specification (design) documents for functional requirements
• Managing existing and creating new automations using Alteryx, Python, SSIS
• Creating reports and dashboards in Power BI

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Managing day-to-day operations of Databricks data pipelines, including monitoring, troubleshooting, and performance tuning
• Maintaining Delta Lake data layers (bronze / silver / gold), ensuring data availability, consistency, and smooth pipeline execution

• Dashboard development for sustainability data visualization
• Data integration from various sources for comprehensive reports
• Client reporting collaboration with sustainability team
• Data analysis to identify trends and insights for sustainability initiatives

adatbázis lekérdezések elkészítése, adathibák feltárása és javítása üzleti igényeknek megfelelő magas szintű figyelem a részletekre az adatinkonzisztenciák, hibák és anomáliák azonosításában és javításában projektjellegű és rendszeres adattisztítási feladatok önálló elvégzése adattisztítási...

• 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

• 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

• 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 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

• Implementing and improving business objects for mobile network infrastructure in backend systems up to the API layer
• Developing and maintaining business objects including data models, backend logic, and APIs
• Collaborating with internal stakeholders considering requirements related to external partners

• Data pipeline development
• Data integration
• Data warehousing
• Data modelling
• Data quality and governance
• Performance optimization
• Collaboration with data scientists and analysts
• Technology selection
• Security and compliance
• Monitoring and troubleshooting

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