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.

Design, build, and maintain backend services for data collection and enrichment using Java and Spring. Own features end-to-end, contribute to API and system architecture, modernize legacy Python systems, optimize performance and reliability, improve monitoring/observability, and support production systems.

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.

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 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.

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.

Design, build, and operate scalable Databricks data pipelines and Lakehouse data models using SQL, Python, and PySpark. Implement ELT/ETL and streaming patterns, data quality checks, Unity Catalog governance, performance optimization, monitoring, documentation, and operational support.

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.

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.

Lead technical design and improvements for a large-scale identity data platform. Prototype and evaluate pipeline changes for cost, performance, and reliability; build consensus and drive implementation; mentor engineers; integrate with broader Mastercard systems and support ML workflows.

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 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.

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

Design, build, and operate high-frequency, event-driven data pipelines into Snowflake; implement reverse ETL; model data with dbt; deploy cloud infra as code; monitor and improve production reliability, latency, quality, and cost; mentor teammates and establish data engineering standards.

Design and deliver data-driven solutions by partnering with subject-matter experts; develop data pipelines, ML models, and visualizations; track solution impact using attribution methodologies and manage technical communications in a knowledge management system.

Lead design and development of backend APIs and front-end components for a Risk & Analytics platform. Implement FO/risk requirements, code, test, debug, monitor the platform, collaborate across teams, and mentor junior engineers. Support data visualization and integrate financial models and data pipelines for risk management and asset valuation.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Design, build, and own end-to-end data pipelines on BigQuery and dbt; orchestrate workflows with Dagster; enable analytics and AI use cases; build marketing attribution and reverse-ETL; enforce data quality, observability, and platform standards.

Build and scale a blockchain data platform handling petabytes of on-chain data. Design and implement distributed systems, data ingestion/decoding pipelines, and performant SQL processing. Write production code (Kotlin, Go, Java, Rust), improve developer experience, automate operations (including AI-driven automation), and own platform components.

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.

As a Senior Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Build and operate large-scale data pipelines and orchestration for generative AI research, focusing on video/audio datasets, feature extraction, labeling, and dataset quality to improve model performance.

Build and maintain high-performance, fault-tolerant distributed backend services and data pipelines for large genomic and health datasets. Design storage, indexing, and async event workflows; optimize latency, throughput, and reliability. Partner with bioinformatics and product teams to validate scientific accuracy and guard AI-driven responses.