Top Data Engineer Jobs in Romania

Design, build, and manage batch and real-time data pipelines on GCP. Implement Terraform IAC, CI/CD, APIs, and CDC ingestion via Datastream. Build medallion architecture with Dataform/dbt, optimize BigQuery and ClickHouse models, create Airflow DAGs with monitoring, and maintain GDPR/CCPA compliance and data governance.

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

The Senior Data Engineer will lead design and implementation of data flows, mentor a team, and drive data initiatives while ensuring effective data engineering practices.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Lead migration from Snowflake to the client platform, build AI-native data migration capabilities, design and maintain scalable data pipelines and platforms, propose improvements, and collaborate with senior engineers, product/project managers, and data analysts.

Design, build, and operate high-frequency, event-driven data pipelines into Snowflake; implement reverse ETL; model data with dbt; deploy cloud infra as code; monitor and improve production reliability, latency, quality, and cost; mentor teammates and establish data engineering standards.

Lead and mentor a data engineering team to translate business analytics needs into scalable data models and pipelines. Design and optimize SQL, build code-based pipelines with Python and Spark orchestrated by Airflow, champion data quality and testing, bridge platform engineers and business stakeholders, and deliver analytics solutions on schedule with minimal tech debt.

Design, build, and maintain scalable data pipelines and ELT/ETL processes on GCP (BigQuery). Handle ingestion, transformation, orchestration, monitoring, performance tuning, and delivery of production-grade data products. Collaborate with analytics engineers, architects, and stakeholders to ensure migration success and long-term platform sustainability.

Design, develop, and deploy Power BI solutions and data models; optimize reports, dashboards, SQL and DAX performance; manage data ingestion, ETL, batch and near-real-time processing; improve platform quality and scalability; cross-train team members; follow software engineering best practices and Agile processes to deliver high-quality data solutions for a global tax and financial automation platform.

Build and maintain AWS-based data platform capabilities, create streaming and batch data products, define data contracts, debug pipelines and batch jobs, promote best practices, and collaborate with stakeholders to resolve pipeline and contract issues.

Own and scale the ingestion pipeline and backend abstractions for high-throughput AI tracing data. Optimize ClickHouse schemas and queries, operate Langfuse Cloud and self-hosted deployments, and build infrastructure-heavy features that enable product engineers to ship data-heavy capabilities.

Lead robotics programming solutions and design automation processes to enhance manufacturing efficiencies, translating business needs into technical specifications while collaborating with cross-functional teams.

Design, build, and own end-to-end data pipelines on BigQuery and dbt; orchestrate workflows with Dagster; enable analytics and AI use cases; build marketing attribution and reverse-ETL; enforce data quality, observability, and platform standards.

The Staff Data Platform Engineer will architect and engineer a cloud-native data platform on AWS, focusing on ETL/ELT pipelines, automation, monitoring, and data governance while collaborating with various teams and mentoring other engineers.

Design, deploy, test, and maintain control system projects for data center and mission-critical facilities. Develop design documentation, perform bench testing and commissioning of PLC/HMI/SCADA programs, support onsite and remote startups, QA/QC installations, and communicate progress with project management and clients. Travel to client sites for implementation and commissioning.

Design, build, and scale ETL/ELT and real-time data pipelines for AI workloads (RAG, fine-tuning, batch inference). Transform unstructured data into vectorized formats, manage feature stores and vector databases, enforce data quality/governance, integrate event systems (Kafka), and collaborate with ML and engineering teams.

Lead Finance data engineering: own end-to-end pipelines for financial and regulatory processes (IFRS 17), ensure scalability, auditability, quality and governance, design large-scale processing, document lineage and models, provide hands-on technical leadership, mentor engineers, and collaborate with finance, actuarial, risk and AI stakeholders to evolve data engineering practices for analytics and AI.

Lead delivery of data and content migration projects, implement data governance and quality solutions, review and improve migration tools, provide technical plans and troubleshooting, act as SME for content migrations, and manage risks across multiple projects while collaborating with clients and delivery teams.

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 Software Engineer, you'll design and build scalable market data systems, improve API architecture, and enhance overall system performance, contributing to Alpaca's infrastructure for trading financial assets.

Seeking a Senior Data Support Engineer with 5-6 years of experience in Data Engineering, specifically utilizing Snowflake, Python, SQL, and AWS for data manipulation, warehousing, and testing processes.

The Senior Data Engineer will develop data solutions, build ETL processes, ensure data quality, and collaborate with the team on data analytics projects.

Lead development of SQL-heavy ETL/ELT pipelines and Snowflake data warehousing using Python, dbt, and AWS (Glue/Lambda/S3). Ensure data integrity, perform root-cause analysis, optimize data lake architectures, and produce QuickSight visualizations for stakeholders while collaborating across teams.

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.

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