Python developer állások XII. kerületben (adatbázisszakértő)

• Adatmigrációs folyamatok áttekintése, fejlesztések kivitelezése
• SQL, PowerShell, Python programozói feladatok ellátása
• Üzleti folyamatok feltérképezése, hatékonyságának javítására való javaslattétel
• Fejlesztési specifikációk elkészítése, fejlesztési dokumentáció
• Ellenőrző, támogató riportok készítése

• Maintaining and evolving existing data platform
• Building processes to ingest data from Kafka, APIs and Databases using AWS MSK Connect
• Development and maintenance of real-time data processing applications using frameworks like Spark Structured Streaming and Kafka Streams

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...

• Üzleti alkalmazások operatív támogatása: jogosultság-beállítás, működési kérdések megválaszolása, hibajegyek önálló kivizsgálása és lezárása
• Komplex SQL lekérdezések és pontos, biztonságos adatjavító scriptek írása éles adatbázison (MS SQL/ MySQL / Firebird / PostgreSQL)

• 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

nemzetközi környezetben dolgozni, ahol az Erste Csoport 8 országának modellezési csapataival együttműködve fejlesztjük a kockázatkezelési modelleket és módszertanokat...

• Gather and translate business requirements into data-driven solutions
• Create and maintain dashboards, reports, and semantic data models
• Ensure data quality, consistency, and usability across reporting solutions

• Design, implement, and maintain scalable BI and data processing solutions
• Develop and operate ETL pipelines for customer, booking, and product data
• Integrate data from various file- and REST-based Magenta APIs
• Generate and deliver reports and datasets for multiple downstream consumers

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs

• Development and operation of data pipelines
• Building data layers in OneDataLake (ODL) Central Data Store Consumer (CDSC)
• Balancing business and IT demands to build modern and efficient pipelines in public cloud environments
• Integration of data preparations into managed processes

• 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

• 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
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

• 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

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• 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

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Collaboration with data owners across departments to establish accurate and complete datasets
• Support for definition, documentation and maintenance of metrics and KPIs across all business domains
• Collection, cleaning, structuring and preparation of datasets for analysis and reporting

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Integration of data ingestion, processing, transformation, and storage

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