Top Data Engineer Jobs in Hungary

Designs, develops, and optimizes scalable batch and streaming data pipelines using Azure Databricks, Spark, Delta Lake, Azure Data Factory, and related Azure services. Responsibilities include data modeling, performance tuning, cluster management, monitoring, governance, security, data quality, CI/CD, documentation, and collaboration with analytics and data science teams. The role also supports machine learning integration, business intelligence, and migration to Databricks as a strategic data platform.

Support development of AI and perception solutions for camera and radar products used in autonomous driving and safety-critical vehicle systems. The intern will work with innovative software technologies, collaborate in an agile international team, and receive mentoring while contributing to autonomous mobility projects.

Build and maintain scalable GCP data pipelines, BigQuery data models, enterprise semantic layers, and CI/CD workflows for a modernized marketing data platform. Rebuild legacy pipelines, support DataHub adoption, enforce data quality, optimize performance and costs, and enable secure multi-brand marketing reporting. Collaborate with product, Martech, analytics, and data engineering teams.

Own and continuously improve Creditstar’s AWS and Snowflake data platform, ensuring scalability, reliability, security, governance, observability, and cost efficiency. Establish engineering standards, manage integrations, support GDPR and PII controls, lead incident resolution, and collaborate with DevOps, BI, analytics, data science, risk, and product teams. The role also supports self-service data capabilities and FinOps practices.

Lead development of Data and AI features from data architecture to optimization and simulation. Design scalable data architectures, reliable pipelines, and DataOps/DevOps workflows. Partner with analysts, product managers and supply chain specialists to turn complex logistics data into actionable solutions.

Lead the architecture and hands-on delivery of an Everything-as-Code data mesh, including Kafka and NiFi event streaming, Kubernetes infrastructure, Terraform and GitOps deployment, schema governance, hybrid lakehouse integration, FinOps optimization, resiliency, and distributed observability across multi-cloud and on-premises environments.

Build and optimize data architectures, databases, warehouses, lakes, lakehouses, ETL processes, and data pipelines. Write SQL and Python, integrate data sources, develop Power BI and Superset reports and dashboards, and evaluate data technologies. Monitor performance, troubleshoot issues, ensure data security and compliance, and deploy infrastructure-as-code and Jenkins-based CI/CD automation while collaborating with engineering teams.

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.

Build and own the architecture for Dune’s curated data lifecycle, including dependency-aware orchestration, backfills, schema evolution, retries, recovery, data quality, and alerting. The role combines backend software engineering with large-scale data systems work across Go, Kotlin, Rust, Python, and SQL. Responsibilities include designing ingestion and curation contracts, making architecture decisions, solving ambiguous problems, and leading work that other engineers can execute.

Design and build durable, distributed data-streaming infrastructure that decouples process data from Camunda’s live execution engine. Develop customer-facing integrations such as Kafka connectivity, support analytics data consumption at scale, and make architecture decisions around consistency, durability, and storage. Participate in production support and on-call rotations while collaborating with Product, Data Layer, Distributed Systems, QA, SRE, and Support teams. Lead ambiguous, cross-functional engineering initiatives from design through delivery.

Build and maintain Camunda 8 backend data-layer services spanning relational databases and Elasticsearch/OpenSearch. Design scalable storage, query, retention, and streaming systems; improve performance, indexing, and production tooling. Lead engineering initiatives from solution design through delivery, collaborate across teams, provide L3 support, and participate in on-call rotations. Investigate production data issues and contribute to schema evolution, workflow automation, and CI improvements.

Provide hands-on Apache Airflow engineering and customer enablement: develop and troubleshoot DAGs, integrate Airflow with data ecosystems and cloud services, support production onboarding, resolve distributed system issues, deliver technical guidance and workshops, and collaborate with customers and internal teams to stabilize and operate a managed Airflow platform.

Own the design, delivery, and operation of complex data pipelines, datasets, and platform components. Translate business needs into scalable data models and reliable data products, improve data quality and observability, resolve production issues, and establish reusable engineering tools and standards. Collaborate with product and business stakeholders, contribute to architecture decisions, mentor engineers, and participate in on-call support.

Designs, builds, and maintains scalable batch and streaming data pipelines, lakehouse medallion architectures, transformation layers, and data models. Develops PySpark and SQL solutions, integrates diverse data sources, implements data quality monitoring, and manages infrastructure as code. Troubleshoots pipeline and data incidents, participates in code reviews, collaborates with architects, and mentors junior and mid-level engineers.

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 maintain scalable batch and streaming data pipelines, internal tools, and APIs to support analytics, product features, and ML. Collaborate with product and engineering to improve data infrastructure, ensure reliability, testing, and observability in a cloud-native environment.

Design and operate the data platform supporting AI products, including data models, storage architecture, APIs, backend services, ingestion pipelines, scoring workflows, and retrieval components. Ensure data correctness, performance, scalability, observability, and reliability across production systems. Collaborate with data scientists, AI engineers, and infrastructure teams to deploy services, resolve production issues, and safely manage schema changes and backfills.

The role involves implementing AI features, improving retrieval quality, collaborating with teams, and building backend APIs for various projects.

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

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.

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.

As a Software Engineer on the data platform team, you'll automate data platform operations, write Python code, and collaborate on solutions within a distributed team.

Design and implement enterprise data quality frameworks for lakehouse platforms. Build automated validation tests, dashboards, anomaly detection, observability solutions, and CI/CD quality checks. Manage data quality SLAs, profile new sources, resolve incidents, collaborate with governance and source owners, and educate engineering and product teams on quality standards.

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