Python developer állások, munkák adatbázisszakértő kategóriában

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• BI alkalmazások fejlesztése (.NET C#, django – python)
• Enterprise Unit belső szervezetei számára eseti és rendszeres riportok készítése
• EDWH (Enterprise Data Warehouse) fejlesztése és új üzleti tartalmak implementálása
• Power BI riportok és dashboardok készítése
• Adatmigráció

• Develop, maintain and optimize Python and Linux shell scripts for data extraction, transformation, and loading.
• Build automated pipelines and reusable code modules to support recurring reporting and analytics workloads.
• Ensure accuracy, completeness, and consistency of datasets.

• Develop, maintain and optimize Python and Linux shell scripts for data extraction, transformation, and loading.
• Build automated pipelines and reusable code modules to support recurring reporting and analytics workloads.
• Ensure accuracy, completeness, and consistency of datasets.

Test approach and ownership: Design and own the test approach for assigned tools, including risk-based scoping, test levels and acceptance criteria....

• 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

• As a Working Student AI Research Engineer for SLM Optimization (m/f/d/x), you will support the team in developing, refining, and managing caching mechanisms for Small Language Models (SLMs).
• You will contribute to the training and further development of models for cache prediction.

Contribute to our Text Analytics and Generative AI projects - from data preparation and analysis through model and prompt evaluation to the development of new features....

• 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

You architect cloud and hardware solutions to scale AI workloads across GPUs and accelerators, while optimizing storage and networking for throughput, resilience, and cost efficiency....

• Oracle, Microsoft SQL Server és PostgreSQL adatbázisok napi üzemeltetése és felügyelete Linux és Windows Server platformon
• Mentések ellenőrzése, visszaállítási feladatok és tesztek végrehajtása
• Felhasználó és jogosultságkezelés, adatbázis objektumok kezelése

• Design, develop, and maintain applications.
• Optimize and enhance existing applications and infrastructure.
• Ability/interest to work with machine learning.
• Collaborate and communicate with various teams within the company.
• Ensure all applications reflect our internal policies and standards.

• 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 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

Analyze AI computing systems end-to-end: Understand how training and inference workloads run on modern data-center architectures and identify the fundamental bottlenecks in compute, memory, interconnects and energy efficiency....

• Define and further develop the Snowflake platform roadmap in alignment with enterprise data strategy and business priorities
• Establish the platform vision and manage priorities, demand intake and business requirements to maximize business value and support strategic objectives

• An opportunity to build the foundation for next-generation products
• The option to write a master thesis following an internship or working student position
• Hands-on work on intrinsic, extrinsic, and multi-camera calibration for ZEISS use cases

• 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

• Technical leadership and mentoring of data engineers
• Technical oversight for Databricks solutions
• Design and implementation of scalable ETL/ELT pipelines using Databricks, Python/PySpark, SQL, and Delta Lake