Top Data Engineer Jobs in Bucharest

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.

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

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.

The Data Engineer role involves creating data pipelines, conducting ETL activities, and transforming data in Azure Synapse and Azure Data Factory. Responsibilities include data ingestion from various sources and orchestrating ETL processes.

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.

Own and improve customer and product data pipelines, CDP and analytics platforms (Segment, Mixpanel, BigQuery, dbt). Build analytics-ready models, replace fragile integrations, enforce data governance, QA, and monitoring, and partner with engineering, product, marketing, and sales to enable downstream reporting and activation.

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

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.

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

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.

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.

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.

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

The Qlik Sense Developer will create applications, manage data modeling, support internal users, and collaborate with teams focused on data visualization.

The Data Engineer will enhance, test, and implement applications, support IT operations, and collaborate with stakeholders to ensure delivery of robust solutions.

The Data Analytics Engineer designs analytics-ready datasets, translates business needs into analytical models, ensures data quality, and collaborates with stakeholders for effective data governance.

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.

The role involves driving AI tooling adoption, developing AI agents, embedding in Scrum teams, and optimizing AI's impact on engineering productivity.

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 Senior Data Engineer designs and maintains data pipelines and AI workflows, optimizing ETL processes for BI and LLM applications.

As a Big Data Platform Engineer, you'll manage and optimize Cloudera Data Platform clusters, ensuring performance and scalability for ING Wholesale Banking's data infrastructure, while automating operations and supporting collaboration across data engineering teams.