Top Data Engineer Jobs in Italy

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, model, and develop AWS-based data ecosystems and pipelines. Gather and document business and technical requirements, optimize data storage (lakes/warehouses), tune performance, troubleshoot processing and infrastructure issues, integrate diverse data sources, mentor junior engineers, and engage directly with clients.

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 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 develop ETL processes, design data protection methods, and contribute to a growing global data landscape in the cloud.

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.

Build the companys first data stack and data products (internal analytics and customer-facing). Work across data engineering, devops, and software tasks; ship early features, improve developer experience, document proposals, and iterate based on feedback.

Design, build, and operate scalable data pipelines and models on GCP. Ingest, transform, orchestrate, and ensure data quality and reliability for analytics and ML. Collaborate with cross-functional data teams, translate business requirements into deliverables, and mentor junior engineers while following development and change-management standards.

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.

Lead foundational data-engineering work to validate and re-engineer pipelines for an anonymized, centralized credit data lake. Harmonize schemas across entities, build dbt models and tests, implement data-quality suites (Great Expectations), entity resolution, anonymization controls, optimize Spark/Glue jobs, orchestrate pipelines (Airflow/Step Functions), and produce documented, feature-ready datasets and runbooks for a regulated UK/Ireland lending environment.

Own end-to-end AI-automated data platform migration projects (1-4 concurrently): scope, plan, execute, and hand off. Act as primary customer contact, configure Datafold's Migration Agent, partner with engineering on execution, and help refine delivery playbooks.

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

Architect and build high-performance spatial data pipelines and scalable backend logic for massive datasets. Optimize geometry storage, implement spatial indexing, work with OLAP databases, and lead a technical team through code reviews, mentoring, and technical leadership.

Design, build, and maintain scalable data pipelines and platforms for analytics. Develop workflows to ingest, parse, and process structured and unstructured data. Collaborate with cross-functional teams to support reporting, analytics, and mission-driven use cases.

As a data engineer, you will organize and analyze structured and unstructured data, develop pipelines, and collaborate with a multi-disciplinary team to create solutions for data-driven insights.

The role involves managing data transformation and reporting pipelines, automating data processes, and performing data analysis while collaborating with business owners. The candidate will use tools like Power BI and SQL in their tasks.

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.

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.

Lead technical solution architecture and application engineering for data center automation using robotics and partner technologies. Support presales, shape proposals, drive system integration, and ensure smooth transition from concept to execution. Capture feedback to improve standardized solutions and contribute to next-generation, AI-enabled automation concepts.

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.

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.

As a Data Analytics Engineer, you'll design and maintain ETL pipelines, ensure data quality, and collaborate with various teams to meet data needs.

Design and maintain data warehouse systems, develop ETL pipelines, manage datasets for analytics, and implement real-time data solutions.