Top Data Engineer Jobs in Romania

Build and operate globally distributed, fault-tolerant cloud platform services for a query engine ecosystem. Design, implement, and scale microservices integrating Cassandra, Kafka, Elasticsearch/OpenSearch and other data stores. Mentor engineers, contribute to architecture, ensure data availability/security, and collaborate across teams to turn prototypes into production-grade services.

Design, build, and maintain scalable GCP data pipelines and ETL/reverse ETL processes using Dataflow, Dataform, and BigQuery. Develop secure APIs for ingestion, optimize data models and Datastream integrations, implement monitoring, and ensure GDPR/CCPA-compliant data governance for player analytics and fraud detection.

Design, build, and maintain large-scale cloud-native data pipelines and lakehouse/warehouse solutions using Databricks, Spark/PySpark, Delta Lake and Snowflake. Collaborate with architects, product owners and data teams to implement ETL, data quality, governance, MLOps (MLflow) and BI integrations while ensuring best-practice CI/CD, version control and operational reliability.

The Senior Product Data Engineer will build, iterate, and launch data products, focusing on large-scale data processing and ETL/ELT pipelines, using various technologies and implementing AI features.

As a Data Engineer, you will design and manage scalable data pipelines, process various data types, collaborate with Data Scientists, and contribute to team knowledge-sharing.

Design, build and support AWS & Snowflake cloud data platform and business tenancies. Implement automated data pipelines, migrate legacy data, and develop event-driven streaming solutions using Kafka. Collaborate with product teams, ensure CI/CD with GitLab, write automated tests, operate within Agile and ITIL 2nd/3rd line support.

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.

The Manager of Data Science will lead a team focused on AI innovations utilizing LLMs, provide mentorship, and align technical strategies with business goals.

The Python Data Engineer is responsible for designing and managing data pipelines using cloud technologies, processing large-scale data, and collaborating with Data Scientists. Key responsibilities include ETL/ELT development and data architecture.

Support the MMB Analytics team's solutions by monitoring data loads, triaging bugs, and collaborating with development on troubleshooting. Document findings and assist with release tasks.

Design, build, test, and deploy cloud application solutions and platform/infrastructure environments. Integrate cloud and non-cloud systems, create proofs of architecture, and work within agile teams using Python, AWS, Terraform, and containerization technologies.

As a Senior Software Engineer at CrowdStrike, you'll build scalable cloud systems with a focus on microservices architecture while collaborating on data platform components and enhancing security services.

Build, maintain, and scale ELT/ETL data pipelines and dbt models on Google BigQuery. Write Python for data processing and automation, ensure data quality, monitor pipelines, troubleshoot issues, and collaborate with analytics, product, and game teams to deliver reliable analytics datasets and contribute to data architecture.

The Data Engineer will build and optimize data pipelines, integrate data sources, enhance analytics platforms, and collaborate with teams to deliver data solutions.

As a Junior Data Engineer, you'll design and implement data pipelines, improve ETL processes, manage analytics platforms, and communicate with stakeholders.

The role involves designing data pipelines, managing databases, ensuring data quality, and implementing data governance policies while using various technologies and advising clients.

The Data Engineer will build and maintain data pipelines, ensure data quality, and support advanced analytics with a focus on AI-driven use cases.

Operate and support Kafka clusters (MSK and on-prem), manage Kafka Connect ecosystem (Debezium, KSQL, Schema Registry), troubleshoot producers/consumers, implement HA/backup strategies, automate provisioning (IaC/scripting), monitor and tune cluster performance, support incident response and on-call, and document operational procedures.

Design and build real-time data pipelines using ClickHouse and Google Cloud. Focus on data quality and optimize financial datasets for analytics.

The Data Engineer designs, implements, and monitors security controls for cloud and on-premises infrastructure, ensuring resilience against cyber threats and compliance with regulations while collaborating with teams.

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

The Middle Data Engineer will design and develop data pipelines using Azure Databricks and maintain Lakehouse architectures, integrating with SQL Server data warehouses while ensuring data quality and performance optimization for analytics.

The Senior Data Engineer will design and build scalable data pipelines, modernize data architectures, ensure data quality, and collaborate with cross-functional teams to transform business requirements into data solutions.

Design, build, and maintain scalable data pipelines on GCP; optimize data models; ensure data quality; support legacy data migration; collaborate with teams; implement monitoring; contribute to data governance best practices.