Python állások V. kerületben (adatbázisszakértő)

• 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,

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

• 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

• 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,

• 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

• 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,

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 various sources for comprehensive reports
• Client reporting collaboration with sustainability team
• Data analysis to identify trends and support sustainability initiatives
• Quality assurance of data in dashboards and reports

• 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

• 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

• Tackling complex technical challenges focused on scalability, reliability, and speed
• Maintaining a high-performance infrastructure that processes millions of events with low latency
• Collaborating with Data Scientists and Engineers to design and implement cutting-edge feature topologies

• 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

Performing tasks related to the position....

• Data ingestion processes from various sources into the Data Lake
• Design, development and optimization of complex data pipelines for reliable data flow
• Build, development and maintenance of frameworks facilitating construction of data pipelines

• Build and maintain dataset ingestion, cleaning, and versioning pipelines
• Design and operate labeling workflows including quality control and inter-annotator agreement tracking
• Own dataset testing including coverage analysis, class balance, leakage detection, and dataset documentation