Top Data Engineer Jobs in Hungary

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

The Data Engineer will develop and optimize data pipelines for NPS programs, enrich survey data, ensure reliable workflows, and collaborate in an agile team.

The Senior Cloud Data Engineer designs and implements data solutions on AWS, optimizing data pipelines, writing SQL and Python code, and managing deployments with DevOps practices.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

Manage Online Data Engineer teams, oversee data infrastructure, prioritize projects, and develop advanced analytics aligned with business objectives. Provide leadership and mentorship while ensuring high performance and effective team collaboration.

Build and optimize data pipelines in Snowflake, automate transformations, and collaborate with technical and business teams to meet project requirements.

As a Data Engineer, you'll design and maintain ETL pipelines, write TypeScript code, and collaborate with stakeholders to ensure data quality and performance.

As a Backend Engineer, you'll lead technical problem-solving in data engineering and machine learning, improving risk assessment tools and features.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

Develop data platforms, collaborate on financial projects, and manage high data volumes while ensuring compliance and effective error handling.

The Data Engineer will build ETL/ELT pipelines, manage AI model training datasets, and create automated evaluation pipelines, focusing on AI integration.

As a Data Engineer, you'll design and develop features for a new Data Platform utilizing AWS, data processing tools, and machine learning concepts. You'll collaborate with cross-functional teams, ensure quality deliverables, and leverage AI tools for coding and debugging.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Data Engineer will design and maintain data pipelines, collaborate with cross-functional teams, and implement data quality measures for machine learning models.

The Staff Software Development Engineer will lead cross-functional teams, design cloud-native products, mentor engineers, and ensure system scalability and reliability.

The role involves optimizing AI and data processing for fintech solutions, focusing on AI orchestration, document processing, NLP integration, and quality assurance of systems, requiring relevant experience in data science and LLMs.

As a Senior Data Engineer, you'll deliver complex projects using Apache Spark/Databricks, manage customer relationships, mentor junior engineers, and contribute to team success.

As a Backend Engineer (Data Engineering), design and build scalable data pipelines and infrastructure for processing security data, ensuring reliability and performance.

Join Zencore as a Senior Data Engineer, leveraging Google Cloud expertise and technology strategies to assist clients with data and application modernization.

The Data Engineer designs and implements data infrastructure, ETL/ELT processes, manages data pipelines, ensures data quality, and supports data-driven decision making.

Design and build scalable data lifecycle solutions on Azure, manage data pipelines, and ensure quality and reliability of data applications in collaboration with business units.

As a Senior Data Engineer focused on QA, you will validate ETL processes, design test cases, and ensure data reliability across platforms.

Design, develop, and maintain scalable data-driven applications, support deployment and monitoring, and mentor team members while aligning projects with business requirements.

Design, develop, and maintain software systems for data collection pipelines, lead backend component development, mentor engineers, and improve system reliability while collaborating with teams.