Top Data Engineer Jobs in Italy

Build and maintain scalable data pipelines, transformations, and analytics-ready models using dbt, SQL, Python, and Snowflake. Implement ingestion, CDC, API integrations, testing, monitoring, and observability. Collaborate with analysts and stakeholders to define metrics, ensure data governance and compliance, and optimize data platform reliability.

Build and own Python ML data pipelines, feature store design, and model serving infrastructure. Implement data quality and drift detection, establish reusable pipeline patterns, and operate production data systems to support ML training and inference.

Develop, test, debug, and optimize embedded firmware for Data Center SSD controllers and memory systems. Troubleshoot and perform root-cause analysis, collaborate with cross-functional teams on integration and validation, participate in code reviews, and support performance profiling and failure analysis.

Design, build, and maintain scalable data pipelines, warehouses and lakes; ensure data quality, security, and performance; enable analytics/ML deployment; collaborate across multi-site teams and support governance and delivery.

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 Junior Data Engineer will design and optimize data infrastructure on GCP, focusing on ETL/ELT pipelines and ensuring data quality, governance, and security.

The Data Engineer will develop and maintain data applications, create workflows for data processing, and collaborate with a team to build advanced technology solutions. Requires 2+ years of experience and TS/SCI clearance.

Design and build agentic systems and production infrastructure for an AI-driven financial intelligence platform. Integrate LLMs, manage prompts and tool-calling, develop RAG and retrieval systems, build MCP servers and observability, run LLM evaluation pipelines, optimize performance and cost, and mentor junior engineers.

Build, operate, and optimize scalable ETL/ELT data pipelines and data warehouses across cloud platforms. Ensure data quality, lineage, security, and governance; integrate diverse sources; enable AI/ML and analytics via APIs, CI/CD, and orchestration. Collaborate with architects, data scientists, PMO, and privacy teams to support global automotive knowledge systems.

As a Data Engineer, you will develop and maintain data pipelines and workflows, collaborate with teams, and create solutions for data processing and analytics.

As a Senior Data Engineer, manage and develop complex data applications, create ETL workflows, and ensure data platforms are scalable while collaborating with a multi-disciplinary team.

As a Data Engineer, you will develop ETL processes, design data protection methods, and contribute to a growing global data landscape in the cloud.

The Junior Data Engineer will build and maintain data infrastructure for business decision-making, create ETL processes, and develop dashboards for analysis.

The Freelance Mid-Senior Data Engineer will design and optimize data pipelines, manage data flows, and collaborate with the AI team on automation solutions.

As a Data Engineer, you will design and maintain data pipelines, ensure data quality, optimize database performance, and collaborate with data teams to enhance data accessibility and processing.

As a Data Engineer, you will build and maintain data pipelines, improve data warehousing, and enable data-driven decisions by collaborating with engineering, data science, and analyst teams.

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

Design and specify data handling and command-and-control system architectures, perform integration, verification and validation (IVVQ), define test plans and procedures, carry out system-level testing, and demonstrate solutions to customers while ensuring technical coherence across interfaces.

The role involves designing, developing, and validating software applications for satellite test systems, managing virtual environments, and building data pipelines for satellite data processing.

Build and maintain internal web applications and lightweight APIs (Flask/FastAPI) for analytics; perform data extraction, cleaning, statistical modeling, and interpretability-focused models for manufacturing in a GMP context; collaborate with engineers, scientists, and quality partners; use git, testing, documentation, and platform/DevOps practices to operationalize models and deliver auditable, production-ready analytic solutions.

Own and evolve a GCP-native data platform from ingestion to reporting. Lead architecture, reliability, observability, data quality, cost optimization, and AI-assisted engineering practices while mentoring engineers and collaborating with product and customer teams.

The Software Engineer will operate and enhance the cloud infrastructure, manage data ingestion, collaborate with scientists, and contribute to data processing and infrastructure for AI model training.

This role focuses on data collection for model training, managing the ingestion pipeline on GCP, and collaborating with the AI team to enhance data quality and efficiency.

The Software Engineer will manage data collection, build ingestion pipelines, and ensure high-quality datasets for model training, collaborating with AI scientists.