Senior engineer állások XII. kerületben (adatbázisszakértő)

• Design, build, and maintain robust data pipelines that are scalable, efficient, and meet business needs
• Collaborate with cross-functional teams to understand and translate business requirements into data solutions

• Learn data engineering principles
• Learn to design and implement ETL processes and pipelines
• Work with SQL, Python and different programming languages and notebooks
• Learn Power BI report building, Data Bricks and various ETL tools

• Design, development, and continuous improvement of the Data Warehouse environment 
• Development and optimization of ETL processes
• Administration and operation of complex SQL cluster environments 
• Re-engineering and modernization of existing SQL cluster architectures

• üzleti specifikációk és szakmai iránymutatások alapján a vállalati adatmodellek megtervezése, módosítása és fejlesztése
• felhőalapú és on-premise adat-infrastruktúra fejlesztése és karbantartása
• automatizált élesítési és deployment folyamatok kialakítása és működtetése az adatplatformhoz kapcsolódóan

• Learn Generative AI principles and models
• Learn Large Language Models, Natural language processing
• Work with Different generative AI Tools and uses
• Learn the LLMs, NLP fundamentals, Transformers, and attention mechanism
• Build Custom dataset for LLM, Build your own custom chatbot/AI bot/custom GPT

Design various RESTful APIs and backend databases in multi region environment. Contribute into targeting engine and segmentation pipelines. Develop automations and tests to ensure system stability. Collaborate with various Engineering and Business teams on their needs. Drive innovation in Data...

Design and build scalable data pipelines that support AI-enabled digital experiences, personalization, and marketing automation. Leverage AI-driven development and testing tools to increase engineering quality, speed, and reliability. Contribute to ongoing platform modernization efforts across...

Design, implement and enhance data solutions for customer organizations Implementation of data integrations (e.g. load data from operative systems like ERP or CRM) Development of data platform / data warehouse in cloud platforms (e.g. data transformation and aggregation) Implementing...

Creation of Python code, tests, and modification of GitHub Action CI/CD pipelines Working with AWS-based infrastructure and Docker containers Combining software and data engineering skills to deploy, debug, and run systems Delivering and scaling AI solutions embedded in cross-functional teams...

Deliver complex data engineering projects individually or by leading small delivery teams Work with EMEA and US customers to solve data engineering, ML, ML Ops, and cloud migration challenges Set up new data architectures from scratch Guide customers through adopting the latest technologies Manage...

Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals. Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing,...

Design, implement, and manage Azure cloud infrastructure to support Databricks and data platform workloads Build and maintain Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory (AAD) integrations Implement Infrastructure as Code (IaC) using...

Design, write and execute comprehensive test plans, test cases and test scripts to validate ETL/data‑pipeline processes, data transformations, and data integrity (source‑to‑target, cross‑reference, reconciliation). Validate data extraction, transformation and loading processes for accuracy,...

Design predictive models Conduct large-scale experiments Uncover insights that inform decision-making Define and develop ontologies and knowledge graphs to connect and contextualize enterprise data Establish data standards and maintain data quality Operationalize models and graph services at scale...

Build and refine backend services and data pipelines Develop reliable Python workflows/services and relational database solutions for high-quality data delivery Lead technical design for complex roadmap work-data collection, analytics and distribution Improve reliability and scalability of...

Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage) Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability...