Senior Data Engineer
Design and optimize complex SQL Server solutions with a focus on performance tuning and data modeling. Automate processes using PowerShell and integrate systems via APIs and LLM-driven workflows.
Remote Data Engineer Jobs in Hungary
90 Data Engineer jobs in Hungary available for remote work from home. Apply for positions such as Senior Data Engineer, Senior Data Engineer, Senior Structural Engineer - Data Center and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and optimize complex SQL Server solutions with a focus on performance tuning and data modeling. Automate processes using PowerShell and integrate systems via APIs and LLM-driven workflows.
Build and maintain resilient streaming and batch data pipelines to ingest, normalize, and distribute market and trading data. Develop self-serve tooling and data governance frameworks to ensure high-quality, observable, and performant data products across the organization.
The Senior Structural Engineer will independently manage engineering and project management tasks for small to medium-sized projects from start to finish, including processing design calculations and developing project scopes and schedules. Responsibilities also involve producing structural construction drawings and specifications, and coordinating efforts with other internal teams and clients.
The role involves leading the development and maintenance of data services and solutions to support products, downstream services, or infrastructure tools used across BEES. This includes designing efficient data models and implementing architectural improvements to enhance performance, monitoring, and evolution of data products.
Design, deploy, and operate scalable data platforms using cloud-native technologies and automation. Collaborate with cross-functional teams to ensure system resilience, performance, and cost efficiency through SRE and DevOps practices.
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You will build and optimize large-scale data pipelines to support AI model training and next-generation product development. You will also collaborate with AI scientists to discover new data sources and ensure the scalability and efficiency of data-processing systems.
You will build and optimize large-scale data pipelines to support AI model training and next-generation product development. You will collaborate with AI scientists to discover new data sources and ensure the scalability and quality of training datasets.
You will build and optimize large-scale data pipelines to support AI model training and next-generation product development. This involves discovering new audio data sources and collaborating with AI scientists to improve data quality and system scalability.
You will build and optimize large-scale data pipelines to support AI model training and next-generation product development. You will also collaborate with AI scientists to discover new data sources and ensure high-quality, scalable data processing.
Design, develop, test, document, and support secure external integrations, including APIs, file-based interfaces, ETL processes, and Snowflake data products. Lead technical delivery and provide production support, stakeholder coordination, code reviews, and mentorship for integration initiatives.
You will build and maintain a core ingestion engine capable of overcoming complex platform defenses to deliver large-scale data. This involves designing distributed pipelines, managing storage environments, and implementing automated monitoring for evasion recovery.
The Data Migration Engineer oversees and executes the migration of clinical and administrative data between Radiology Information Systems while ensuring data integrity and regulatory compliance. They collaborate with cross-functional teams to map legacy data, perform ETL processes, and provide post-migration support for system go-lives.
You will own the architectural execution and hands-on delivery of high-throughput, asynchronous event-streaming infrastructure and hybrid data pipelines. This involves managing multi-cloud environments using declarative code and ensuring robust schema governance and telemetry.
Design, deploy, and maintain secure, highly available Kafka clusters within an AWS environment. Collaborate with development teams to implement best practices for microservices and streaming data pipelines.
The role involves administering and optimizing enterprise Big Data platforms and their underlying infrastructure using automation and AI-assisted tools. You will be responsible for managing Linux systems, databases, and containerized environments while ensuring high availability and performance.
The role acts as a technical owner for customer-facing data workflows, integrations, and AI-driven automation. Responsibilities include designing technical solutions for customers, building internal tooling, and translating customer patterns into product requirements.
Set the technical direction for ingesting, transforming, and delivering healthcare data at scale on a FHIR-based platform. Lead the implementation of AI-native engineering practices and mentor senior and mid-level engineers.
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This role focuses on building and validating PSCAD models to demonstrate reliable grid performance and meet utility requirements for large-scale data center projects and utility interconnections. The engineer will evaluate system behavior during various disturbances in collaboration with internal teams, utilities, and manufacturers, supporting model reviews through commissioning.
You will design, build, and maintain production systems, including evaluation harnesses and data pipelines for AI models. You will also develop APIs and backend services to support human-in-the-loop workflows and improve system observability.
Design and implement data models and ETL/ELT pipelines to integrate complex commercial pharmaceutical datasets. Develop curated datasets, semantic layers, and standardized KPI logic to support field, brand, and patient analytics.
The role involves implementing access controls, data governance policies, and security frameworks across the platform. You will also deliver data lineage, audit, and monitoring solutions while collaborating with business teams to ensure compliance.
The role involves analyzing large datasets to generate actionable business insights and developing analytical solutions. You will manage end-to-end analytical projects while collaborating with cross-functional stakeholders to translate business needs into data-driven recommendations.
Perform startup and commissioning of modular data center equipment while conducting on-site technical diagnostics and root cause analysis. Document test results, produce site reports, and provide operational training to customers.
The role involves owning end-to-end coding data projects to teach frontier AI models how to code. This includes designing agentic training workflows, evaluation rubrics, and technical environments that mirror real-world software engineering.
Own end-to-end coding data projects to train frontier AI models, designing agentic workflows and evaluation schemes. Collaborate with clients and internal teams to build technical environments and rubrics that reflect real-world software engineering.
The role involves designing, building, and maintaining scalable BigQuery datamarts and analytical tables to support BI reporting. You will also develop data pipelines and transformation workflows while ensuring data quality and governance across the environment.
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The role involves designing, developing, and maintaining reliable production-grade ETL/ELT pipelines while ensuring data quality and consistency. You will collaborate in an agile environment to investigate system issues, perform root-cause analysis, and support critical data engineering activities.
Lead a team of data engineers to build and mature a Snowflake-based data platform and dbt modeling layer. Own the technical roadmap for the cloud data stack and partner with stakeholders to transform raw data into reliable assets.
Lead the technical direction and roadmap of the data platform while remaining hands-on in building critical components. Mentor a team of data and analytics engineers and collaborate cross-functionally to implement new data analytics workloads.
Lead the technical delivery and operational reliability of domain-based data products within a unified data platform. Partner with business domain leads to translate priorities into scalable, reusable data engineering solutions.
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