Top Data Engineer Jobs in Romania

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

Design, model, and develop AWS-based data ecosystems and pipelines. Gather and document business and technical requirements, optimize data storage (lakes/warehouses), tune performance, troubleshoot processing and infrastructure issues, integrate diverse data sources, mentor junior engineers, and engage directly with clients.

Design, build, and manage batch and real-time data pipelines on GCP. Implement Terraform IAC, CI/CD, APIs, and CDC ingestion via Datastream. Build medallion architecture with Dataform/dbt, optimize BigQuery and ClickHouse models, create Airflow DAGs with monitoring, and maintain GDPR/CCPA compliance and data governance.

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.

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.

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.

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

Design, build, and maintain scalable data pipelines on Databricks for analytics and AI/ML. Implement ETL/ELT, medallion-style models, CI/CD and orchestration, ensure data quality, governance, security, performance, and troubleshoot production issues while collaborating with cross-functional teams.

Design, build and maintain ETL/ELT data pipelines for structured and unstructured data in Azure using Databricks or Microsoft Fabric. Use Python, PySpark and SQL for processing, contribute to data integration, modeling, quality and provisioning, apply Lakehouse/Medallion architectures, and collaborate with colleagues and clients to deliver maintainable data solutions.

Build and maintain cloud-based media data pipelines and user-facing data products. Design, deploy and govern BigQuery/DBT pipelines, APIs and dashboards, ensure data quality/security, manage vendors, and drive product-oriented delivery and adoption.

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.

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

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 Senior Data Engineer will design and maintain data pipelines, develop ETL processes, optimize GCP services, ensure data quality, and collaborate with stakeholders.

Design and develop Azure Databricks-based data pipelines and Lakehouse architectures using PySpark, Spark SQL, Delta Lake, and Azure Data Factory. Integrate and optimize data from multiple sources, support SQL Server/SSIS platforms, ensure data quality and scalability, and collaborate with BI teams for analytics and reporting.

Design, build, and maintain cloud-based data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate data from multiple sources, optimize large-scale processing, support SQL Server/SSIS environments, and collaborate with BI teams for analytics and reporting.

Design, build, and maintain cloud data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate data from multiple sources, optimize large-scale processing, support SQL Server/SSIS platforms, and collaborate with BI teams for analytics and reporting.

Design, develop, and maintain cloud data pipelines and Lakehouse architectures using Azure Databricks, PySpark, Delta Lake, and Azure Data Factory. Integrate multiple data sources, optimize large-scale transformations for performance, support SQL Server/SSIS environments, and collaborate with BI teams for analytics and reporting.

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.

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.

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

Build and maintain cloud-based data lakehouse pipelines using SQL-driven transformations. Harmonize, model, and prepare data for analysis, reporting and AI. Ensure data availability, integrity, security, monitoring and performance. Collaborate with cross-functional teams, share knowledge, and adopt modern Data Engineering and DevOps practices.

Design, build, and optimize low-latency, high-throughput real-time data pipelines and event-driven architectures. Implement, monitor, and maintain streaming processing systems, ensure data quality and reliability, integrate multiple data sources, collaborate with platform and ML teams, support troubleshooting and operational excellence, and mentor junior engineers.