Top Data Engineer Jobs in Bucharest

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 scale ad-tech data infrastructure to ingest, normalize, and transform massive log-level and reporting data from SSPs, DSPs, and ad servers. Design ETL/ELT pipelines, data models, and warehouses optimized for real-time analytics, implement data quality monitoring, and support BI and analytics teams while ensuring GDPR/CCPA compliance.

Maintain and scale production data ingestion pipelines processing billions of events, support and optimize complex ETL and streaming workflows, develop platform tools and ML/streaming initiatives, ensure reliability/observability, and assist data scientists and analysts with production workloads.

Design, build, and maintain scalable real-time and batch data pipelines for programmatic ad-tech. Ingest and normalize SSP/DSP/GAM data, develop ETL/ELT workflows, data models for yield and auction analytics, maintain warehouses/lakes, implement data quality monitoring, and ensure GDPR/CCPA compliance while supporting BI and analytics teams.

Design and implement scalable Azure data platforms, develop data pipelines, and support clients with data modernization and governance practices.

Design and build highly scalable, low-latency market data systems and APIs. Implement backend services, influence architecture, maintain test coverage, participate in code reviews, troubleshoot incidents, and occasionally be on-call. Work spans streaming and historical market data endpoints and developer-focused API improvements.

Design, build, and operate Azure-based data platform environments and lead migrations to Azure/Databricks/Microsoft Fabric. Implement IaC (Terraform), Kubernetes platform operations, CI/CD automation, security and governance controls, monitoring/observability, and cost/performance optimizations. Collaborate with data engineers, architects, and stakeholders and produce technical documentation while providing technical leadership during the migration.

Build and optimize scalable ETL/ELT pipelines, design data models, ensure data quality and security, improve pipeline/query performance, implement CI/CD for data workflows, and collaborate with product and analytics teams to enable data-driven decisions.

Conduct 60-minute technical interviews for senior data engineering candidates, evaluate cloud-based data platform architecture, ETL/ELT pipelines, distributed processing, security, data modelling, and communication. Complete scorecards, provide hiring recommendations, and collaborate with recruiters to improve assessments.

Design and maintain data infrastructure, build pipelines for data collection, ensure data quality, and collaborate with stakeholders on data requirements.