Sql developer állások IX. kerületben (ai és automatizáció)

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Design and enforcement of data architecture standards including Delta Lake / Lakehouse architecture and data modeling

• Design, develop, test, document, and deploy high quality Salesforce solutions leveraging Einstein 1 Platform, Lightning Web Components, and modern Apex patterns
• Analyze client specific requirements and define data model to support business, reporting and technical requirements

• 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

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

• Establish data feeds with custodian banks, data vendors, and other service providers
• Support senior leadership, clients, and the broader Data Team in executing analyses and providing data-driven answers to questions
• Fully automate and centralize existing data integration processes

• Leading a data engineering team comprising 5-6 consultants
• Overseeing project delivery
• Managing and mentoring the team
• Ensuring successful execution of data engineering projects
• Ensuring successful execution of ML/MLOps projects
• Ensuring successful execution of cloud migration projects

• Technológiai megvalósítási projektekben való részvétel: folyamatfelmérés, elemzés, technológiai megoldások fejlesztése, dokumentálása és tesztelése
• Kutatási és elemzési feladatok elvégzése különböző új technológiák vonatkozásában
• Társosztályokkal és nemzetközi csapatokkal való kapcsolattartás

• 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

• Writing reusable, testable, and efficient code mainly in Python
• Mastering the integration of user-facing elements developed by front-end developers with server side logic
• Integration of data storage solutions
• Handling security and data protection professionally and precisely

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• Writing reusable, testable, and efficient code mainly in Python
• Delivering great user experience by the development of great user interfaces
• Handling security and data protection professionally and precisely
• Collaborative work to provide technical solutions and implement new software features

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients
• Development of highly scalable services realizing AI/ML functionalities

• Design and build agentic systems that plan, call tools and automate real business workflows
• Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration

• 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

• Leading architecture design
• Driving technology decisions
• Co-creating innovative products
• Mentoring clients to adopt Agile practices and engineering excellence
• Leading project workstreams
• Building scalable solutions using Agile methodologies
• Co-creating products with client teams

• Building and maintaining SQL queries and reports that track bookings, pipeline coverage, and conversion
• Monitoring CRM data quality to resolve issues at the source
• Analyzing pipeline trends and supporting the weekly forecasting review cadence with clean, accurate data

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása

Web alapú vállalatirányítási rendszer fejlesztése...

• 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

• End-to-end AI solution ownership from problem definition through prototype validation and production support
• Partnership with product managers and business stakeholders to translate real-world problems into data science and AI initiatives