Top Data Engineer Jobs in Romania

Design, build, and optimize scalable data platforms using Azure and Databricks. Responsible for developing ETL/ELT pipelines, maintaining data quality, and collaborating with analytics teams.

As an Analytics Engineer, you will design and maintain SQL models for on-chain data, work with transformation tools, and collaborate with engineers on data pipelines.

Design and architect scalable backend services, develop robust governance systems, build SaaS solutions, and mentor junior engineers to enhance IoT platform capabilities.

The Data Engineer will build a creative intelligence pipeline, connecting ad data to ETL processes, enabling time-series queries, and documenting the setup for handoff.

The Data Engineer will migrate and optimize databases for clients, design infrastructure for data extraction and transformation, and collaborate with teams on data needs.

As a Data Engineer, you'll design and maintain ETL pipelines, write TypeScript code, and collaborate with stakeholders to ensure data quality and performance.

Lead and mentor a team of data engineers while architecting and implementing data solutions on AWS. Drive technical direction and project delivery.

The Junior Data Engineer will analyze data, design experiments, build a marketing data stack, and collaborate with teams to improve data access and insights.

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

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

N-iX seeks a Data Engineer with MLOps experience to create scalable ML pipelines, deploy models, and contribute to best practices in data engineering and coding.

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

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

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.

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.

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.

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.

The Senior Software Engineer will develop and scale backend services, manage data pipelines, and ensure system reliability across multi-cloud environments.

The Senior Software Engineer will design and build scalable backend services, improve data pipelines, and ensure system reliability and performance.

The Senior Software Engineer will design and build scalable backend services, integrate data pipelines, and ensure reliability and performance in a multi-cloud environment.

The Senior Software Engineer will design and build backend services, work on data pipelines, and ensure system reliability and performance in a multi-cloud environment.

As a Data Analytics Engineer, you will build and optimize the data layer, transforming business requirements into reliable datasets using SQL and dbt, while collaborating with analysts and engineers.

The Senior Data Engineer will design scalable systems, automate ML operations, optimize performance, and enhance infrastructure for data processing and monitoring.

Design and maintain data pipelines, collaborate with stakeholders, ensure data quality, deploy infrastructure as code, and optimize reporting solutions.