Technical állások XXIII. 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,

• Translate client needs into technical solutions 
• Design data-driven systems using Databricks and Azure 
• Build ingestion and transformation pipelines using SQL, Python, dbt 
• Automate data workflows 
• Participate in sprint planning and deliver reliable solutions 

• act as process owner of data management regulations and ensure proper fulfillment of defined roles and responsibilities including its enchancement according to business requirements
• support the operation of data management processes and continuously monitor data quality

• Design and implement ETL processes
• Develop and maintain data pipelines to ingest, transform, and load data from various sources
• Ensuring development tasks to support new release of the project/solutions
• Support production issues, or requests
• Ensure data quality and integrity throughout the ETL lifecycle

Act as the key link between business and delivery teams, ensuring alignment with enterprise standards (architecture, security, compliance) and providing clear visibility on progress, risks, and trade-offs to senior stakeholders....

• Design and maintain robust, scalable data architectures
• Build and optimize high‑performance data models for analytics
• Partner with business and engineering teams to shape data solutions end‑to‑end
• Lead data integration, transformation, and migration efforts

Technical and business support for internal and external users of GSCF applications Quick resolution of application issues and leading technical discussions with clients and projects Collaboration with Product, DevOps, and Developers to investigate and resolve reported issues Participation in...

Building and optimizing scalable data warehousing and lakehouse solutions Creating and owning robust ELT pipelines connecting multiple internal and external data sources Designing and implementing data models aligned with industry best practices Contributing to architectural decisions with...

Data exploration, profiling, cleansing, and preprocessing for high-quality datasets Design and management of workflows for storing and retrieving vectorised documents Application of embedding models to build AI-driven solutions Leveraging modern AI and machine-learning techniques including large...

Collaboration with engineers, project managers, technical leads, business owners and analysts throughout the software development lifecycle Design and implementation of new features in the core product’s data platform and suspicious activity identifying mechanism Improvement of resiliency,...

Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform Collaboration with the Architect in design discussions and proposals Building robust, scalable pipelines using Azure Databricks (PySpark / SQL) Integration of data ingestion, processing,...

Managing complex database systems within a global technology ecosystem Building and managing Database hosting capabilities using Infrastructure as Code for all platform needs Building Database Infrastructure Platforms with developers and providing guidance and tooling to handle distributed systems...

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...

Setting technical direction across teams Driving AI-native and cloud-native architecture and long-term system evolution Leading design of secure, scalable MCP hosts and AWS microservices Balancing performance, reliability, and cost in system design Influencing AI adoption through AI first solution...

Delivery on complex data engineering projects across industries Leading small delivery teams Managing customer relationships alone or with a Project Manager Mentoring more junior engineers Evaluating quality of junior engineers' work Contributing to hiring best-in-class data engineers...

Design and propose changes to current data systems including migration paths and modernization strategies for legacy architectures Define and evolve the target architecture for data platforms covering ingestion, storage, processing, and consumption layers Design and implement batch and...