Python developer állások IV. kerületben (adatbázisszakértő)

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...

• 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

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...

• 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

• Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
• Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
• Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect

• 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

• Building and operating scalable data ingestion and CDC capabilities on Azure-based Lakehouse platform
• Developing pipelines in Azure Data Factory and Databricks
• Maturing engineering approach through Python projects and reusable frameworks

• Design, develop, and implement complex and scalable data solutions on the AWS cloud platform
• Design, build, and optimize data pipelines to ensure efficiency and reliability
• Write clean, efficient, and maintainable SQL and Python code
• Develop and maintain shell scripts to support automation

• 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

• 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

• 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

• Measuring performance of multi-channel patient recruitment campaigns across clinical trial portfolios
• Optimizing performance of multi-channel patient recruitment campaigns across clinical trial portfolios

• 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