Python állások, munkák adatbázisszakértő kategóriában

• 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

• Design and implement data models aligned with industry best practices
• Build and optimize scalable data warehousing and lakehouse solutions and ensure data integrity end-to-end
• Create and own robust ELT pipelines connecting multiple internal and external data sources

• 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) – a TRI adattárházának fejlesztése, új üzleti tartalmak implementálása
• Power BI riportok, 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, 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 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

• 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 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

• Build and own scalable data pipelines and integration solutions our data warehouse and data platform.
• Integrate and transform data from ERP, CRM, finance, and other enterprise systems.
• Ensure high standards of data quality, reliability, performance, and operational excellence.

• 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.

Building efficient and scalable ETL/ELT processes to ingest, transform, and load data from various structured and unstructured sources (databases, APIs, streaming platforms) into BigQuery and Cloud Storage...

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.

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....