Python developer állások, munkák adatbázisszakértő kategóriában

• Making architectural decisions and conducting code reviews,
• Mentoring junior developers and leading the team,
• Designing and building scalable AI data pipelines,
• Developing LLMs (Large Language Models) and AI agent systems,
• Efficiently processing large volumes of data using Python,

• Komplex adattárház és üzleti intelligencia igények felmérése, megoldások tervezése, megvalósításának szakmai koordinálása, kapcsolattartás az üzleti területekkel.
• Önálló BI megoldások, operatív és vezetői riportok tervezése és fejlesztése.

• 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

• Operation, maintenance and scaling of database platforms handling terabytes of data
• Design of scalable, reliable database architectures for different workloads and availability requirements
• Support and optimization of databases including PostgreSQL on AWS RDS, ClickHouse, and YugabyteDB

Ready to fast‑track your career and take on real global challenges? ...

• learning state‑of‑the‑art new technologies
• acting as a team member in BI‑focused engagements

• 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

• Lead the design and development of Power BI reporting and analytics solutions for enterprise clients,
• Facilitate workshops and meetings with business stakeholders to understand reporting and analytical requirements,
• Translate business needs into functional and technical specifications,

• Shape and implement the company’s data science strategy and drive innovation, with a primary focus on Generative AI and Agentic workflows
• Identify opportunities to leverage data for business value and impact
• Take ownership of the full technical stack for development and deployment

• nagy mennyiségű adat feldolgozását támogató adatfolyamatok tervezése és fejlesztése,
• adatbetöltési, adattranszformációs és adatminőség-ellenőrzési folyamatok kialakítása,
• adatforrások integrálása, strukturált és félig strukturált adatok kezelése,

• Oracle adatbázisokhoz kapcsolódó fejlesztési feladatok ellátása,
• PL/SQL eljárások, függvények, csomagok, triggerek fejlesztése és karbantartása,
• A fejlesztésekhez kapcsolódó tesztelési feladatok ellátása,
• Elkészült programegységek telepítése,
• adatbázis-struktúrák, táblák, nézetek és indexek tervezése,

Working on the design, development, and production of advanced digital solutions, ensuring seamless integration with existing infrastructure and adherence to enterprise architecture standards and robust delivery lifecycle processes. This includes leveraging expertise in various digital technologies...

• Dashboard development for sustainability data visualization
• Data integration from internal databases, external APIs, and third-party platforms
• Client reporting collaboration with sustainability team
• Data analysis to identify trends, patterns, and insights

• 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

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Design and update of data architecture to ensure a managed and automated process for data flows
• Optimization of data platforms (PostgreSQL) to ensure stable and timely data streams
• Building and continuous optimization of data ETL (Extract, Transform, Load) processes

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• 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

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods

• Maintaining and evolving data structures
• Building new ETL flows and maintaining or improving existing ones
• Designing new data structures and data modelling concepts
• Ensuring data quality by verifying data consistency and accuracy
• Creating data validation methods