Top Data Engineer Jobs in Romania

The Data Engineer will design, build, and maintain data systems and pipelines for analytics and business decisions, ensuring data usability.

As a Middle Data Engineer, you will migrate legacy SQL Server data warehouses to a cloud-based Snowflake environment, refactor ETL processes, and build data pipelines for analytics and reporting.

Responsible for developing backend AI features, integrating machine learning models, building data pipelines, and maintaining AI services within a retail ecosystem.

The Data Infrastructure Developer will design data pipeline architecture, optimize data flow, develop test plans, and support data governance while collaborating with technical 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 migrate legacy SQL Server data to Snowflake, refactor ETL processes, and optimize data movement for analytics.

As a Data Engineer at Screenverse, you'll build ETL pipelines, ensure data quality, and contribute to data strategy in a collaborative environment.

As a Principal Database Engineer, you will architect scalable PostgreSQL solutions, ensuring data reliability, performance, and collaborating with teams to build a robust data platform for GitLab's growth.

As a Middle Data Engineer, migrate SQL Server data warehouses to Snowflake, refactor ETL processes, build data pipelines, and ensure reliable data movement.

As a Data Engineer, you'll design, develop, and implement high-performance data infrastructure and pipelines while communicating effectively with various stakeholders.

The role involves driving end-to-end testing activities, developing test plans, ensuring data quality, and collaborating with various teams to meet business requirements.

The Data Science Engineer will design ML and AI solutions, conduct analyses, support data integration, collaborate with stakeholders, and improve processes to drive business impact.

The Data Engineer will design and maintain ETL pipelines, optimize data models, develop exporters, and ensure reliable data services for the Lambda app in a fast-paced startup environment.

As a Middle Data Engineer, you'll build and manage ELT/ETL pipelines using Snowflake and Airflow, ensuring data reliability while collaborating with BI teams and maintaining data integrity.

The Senior Data Engineer will create cloud-based data pipelines, optimize data ingestion, perform data analysis, and collaborate with teams to improve analytics products.

The Senior Data Engineer will design, build, and maintain DBT models, develop ETL pipelines, and ensure data quality for analytics initiatives.

The Senior Data Quality Engineer ensures data accuracy and reliability by analyzing quality issues, defining rules, and supporting data quality processes and governance.

The Data Quality Engineer ensures data accuracy and reliability, defines quality rules, supports data cleansing, and manages reference data.

As a Senior Data Engineer, you will design and scale data systems, build ETL pipelines, ensure data quality, and collaborate with product, growth, and finance teams to support decision-making and analytics.

Lead the design and implementation of scalable cloud-based data pipelines and architectures, ensuring best practices, compliance, and data quality.

Build and optimize data pipelines and models, monitor cloud data warehouses, and maintain documentation while collaborating with teams.

Designs and implements data engineering solutions, manages metadata structures, analyzes data for client needs, and ensures data quality in projects.

As a Staff Engineer and Team Lead, you will architect scalable backend systems, mentor engineers, and ensure high-quality code for Alpaca's market data suite.

The role involves developing high-quality backend services, maintaining components, participating in architectural improvements and ensuring system scalability while collaborating with various teams.

End-to-end delivery of ML-powered services, involving research, prototyping, production, and operations. Collaborate on product requirements while maintaining high quality and operational excellence.