Top Data Engineer Jobs in Hungary

Design, build, and operate a cloud-native data platform on Kubernetes; support Spark-based processing, platform reliability, AWS and Snowflake integrations, and AI/GenAI initiatives while collaborating with data scientists and engineers.

The Data Engineer will design and operate scalable ingestion pipelines on Azure Fabric, develop Python libraries, and implement best engineering practices. The role requires collaboration with data architects and analytics engineers to deliver data products and ensure governance adherence.

The Senior Data Engineer will design and develop scalable data pipelines, manage data lakes, ensure code quality, and mentor team members using modern data technologies.

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, build, and deploy scalable Databricks Lakehouse solutions and modular data pipelines using Delta Lake. Implement governance with Unity Catalog, automate deployments via DABs and CI/CD, write Python/SQL code, integrate cloud storage and security, and manage technical delivery and documentation.

Design, build and maintain scalable ELT/ETL data pipelines and the Data & Analytics platform. Integrate and transform internal and external sources, define logical and physical data models, ensure high data quality, monitor and resolve pipeline incidents, document processes, and advise on architecture and best practices including lakehouse and big data capabilities.

The AI Systems & Data Engineer will handle data migration, build AI solutions, integrate systems, and automate workflows for HR transformation.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

The Data Engineer will design, build, and maintain data pipelines, work cross-functionally to define data requirements, and ensure data is secure and governed while supporting AI initiatives.

Design, build, and operate large-scale batch and streaming data pipelines to ingest and process real-time maritime data. Implement data quality, governance, observability, and reliability tooling. Collaborate cross-functionally to deliver scalable, secure, and cost-efficient data solutions and participate in Agile delivery.

Lead foundational data-engineering work to validate and re-engineer pipelines for an anonymized, centralized credit data lake. Harmonize schemas across entities, build dbt models and tests, implement data-quality suites (Great Expectations), entity resolution, anonymization controls, optimize Spark/Glue jobs, orchestrate pipelines (Airflow/Step Functions), and produce documented, feature-ready datasets and runbooks for a regulated UK/Ireland lending environment.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

Build, enhance and expand data pipelines to ingest and normalize large datasets for the European power market. Improve APIs, monitoring, alerting, performance and caching. Collaborate with data scientists and market experts to develop features, extend geographic coverage, and support product growth and reliability.

The Principal Data Engineer will improve data pipeline architecture, optimize data flows, and support data projects for various teams in the company.

Combine and prepare data from multiple sources, clean and validate datasets, perform analysis and exploratory data work, and build/test machine learning models in Python. Translate business questions into analytics tasks, present insights to technical and non-technical stakeholders, and collaborate across teams to support reporting and decision-making.

The Data Engineer will design and maintain scalable data pipelines, optimize data infrastructure, monitor data quality, and enable analytics capabilities, ensuring alignment with business goals.

Design, build, and operate enterprise reporting and analytics platforms. Create scalable ELT/ETL pipelines, master data foundations, and lakehouse/warehouse semantic models. Deliver Power BI datasets and dashboards, implement data quality, governance, DevOps practices, and cost-management data solutions. Partner with finance and stakeholders and provide technical leadership across architecture, deployment, and run-state support.

This role involves developing GenAI tools, building data pipelines, enhancing AI automations, and collaborating with stakeholders for technical solutions.

As a Senior Data Engineer, you'll design and implement data pipelines, focus on AI-first workflows, manage data ingestion, and ensure data integrity.

Seeking a Senior Data Engineer to build and manage scalable data ingestion on an Azure platform, focusing on CDC and Python-based frameworks. Collaborate for robust data products while applying engineering best practices.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.

The Staff Engineer will define architecture, lead data pipeline design, ensure platform reliability, and mentor engineers, driving data initiatives and technical standards.

The role involves creating and automating infrastructure features for data platforms using Python, with a focus on distributed systems and collaboration within a global team.

The role involves automating OpenSearch operations by developing features in Python, collaborating with an international team, and providing expertise on data platforms.