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

The Data Developer will design, code, and manage data pipelines, ensuring performance, reliability, and maintainability. Responsibilities include data transformations, monitoring data quality, and collaborating on data architecture with cross-functional teams.

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

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

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 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 and operate scalable Java-based backend services, develop APIs, build data pipelines, and collaborate with cross-functional teams for personalized solutions.

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

Collaborate in a team to develop and deploy big data anti-fraud solutions using PySpark and Python, ensuring code quality and maintainability.

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.

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.

Design and maintain scalable data warehouse solutions in BigQuery, build data pipelines, implement data quality checks, and collaborate with analysts.

The Senior Python Engineer will develop and optimize data pipelines, manage workflows, implement CI/CD processes, and collaborate with cross-functional teams to enhance the AI & Data platform.

The Senior Python Engineer will design and optimize data pipelines, manage workflows using Airflow, and deploy applications in Kubernetes, contributing to a core AI & Data platform and collaborating with cross-functional teams.

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.

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.

As a Senior Data Engineer, you will design and implement scalable data solutions, develop automated pipelines, and support cloud transition using AWS and Snowflake.

As a Big Data Platform Engineer, you will manage and optimize Cloudera Data Platform clusters, automate workflows, and collaborate with teams to enhance data operations.

The role involves designing and implementing large-scale data pipelines on GCP, maintaining production-grade data solutions, and collaborating with engineers on data foundations.

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, develop, and maintain microservices for data ingestion, focusing on scalability and reliability using Java and various big data technologies.

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 design and implement cloud-native data and AI platforms on AWS, build scalable data architectures, maintain ETL/ELT pipelines, and collaborate with teams and customers to deliver effective data solutions.