Data Engineering Jobs in Italy
There are 1,047 open Data Engineering jobs in Italy on freehire right now. 370 of them were posted recently. The skills employers ask for most often are sql, python and cloud.
Salary
| Currency | Period | 25th | Median | 75th | Postings |
|---|---|---|---|---|---|
| EUR | year | €35,325 | €47,000 | €52,500 | 103 |
From postings that disclose pay. Currencies are counted separately, never converted.
Most requested skills
- sql 53%
- python 50%
- cloud 48%
- analytics 38%
- ai 35%
- data-engineering 33%
- azure 32%
- etl 28%
How the work is done
- Hybrid 48 · 5%
- Remote 23 · 2%
- Onsite 3 · 0%
Visa sponsorship offered in 29% of the 17 postings that state a position on it.
Seniority
- Senior 156
- Junior 57
- Lead 38
- Intern 15
- Staff 8
- C-level 7
Who is hiring
- 1000+ employees 176
- 501-1000 employees 85
- 51-200 employees 31
- 201-500 employees 8
- 11-50 employees 7
Python Data Engineer
Builds and maintains data pipelines using Python and Pandas, analyzes datasets in Jupyter Notebooks, and prepares reports with Excel, Power Pivot, and Power Query.
Junior Data Engineer
Builds and maintains data pipelines for a financial project using Python, Spark, SQL, and cloud platforms like GCP or AWS.
Cloud Data Engineer
Design and build cloud-based data pipelines, warehouses, and analytics solutions for clients using AWS, GCP, Azure, Databricks, and Snowflake.
Data Engineer - Milano
Design and build enterprise-grade analytics solutions on Microsoft Azure, transforming business needs into scalable data platforms and guiding clients through cloud transformation projects.
Senior Data Engineer
Senior Data Engineer builds and maintains Azure/Fabric-based data pipelines, ETL workflows, and Power BI dashboards for enterprise clients, ensuring data quality and translating business needs into technical solutions.
Senior Data Engineer
Senior Data Engineer builds and scales a Lakehouse-based data platform with Redshift, dbt, Airflow, and streaming pipelines to power analytics and ML at a fintech company.
Junior Data Engineer
Build and maintain cloud-native data pipelines and frameworks on AWS/GCP to feed AI models and business use cases, using Python, Spark, Docker, and Infrastructure as Code.
Data Engineer - Python
Build and maintain ETL pipelines and data platforms in Python for an insurer, ensuring reliable data flows to support business processes.
Senior Data Engineer
Senior Data Engineer designs and builds scalable ETL/ELT pipelines and distributed data architectures (cloud, on-prem, or hybrid) using Python, PySpark, and SQL for modern data platforms.
Senior Data Engineer
Builds, tests, and maintains data pipelines using Python/PySpark and AWS, with a focus on Databricks and Apache Spark for HR-tech job-matching.
Data Engineer - Bologna
Builds and maintains data pipelines, Data Lake, and analytics infrastructure using Spark, Airflow, Delta Lake, and Parquet to support reporting and business decisions in an energy/utilities company.
Sas data engineer
Develops ETL pipelines and data warehouses using SAS Base 9.4 and SAS Viya 4, writing SQL/PROC SQL and translating business requirements into technical solutions.
IOT & DATA ENGINEER
Designs and integrates IoT and SCADA systems for airport assets, automating data flows and enabling predictive maintenance with industrial protocols and sensors.
Data Engineer - Development & Integration
Design and maintain scalable data pipelines and ETL processes for a mining-sector client, ensuring robust data architecture and integration aligned with business needs.
Data Engineer (Azure Data Platform)
Build and maintain Azure-based data pipelines, lakes, and BI integrations using Data Factory, Data Lake, SQL, and Power BI.
Data Engineer III (Remote)
Designs and builds scalable data pipelines and cloud-native systems using Hadoop, Spark, Java, and IaC tools to enable data-driven architectures.
GCP Data Engineer: Scale ETL Pipelines | Remote
Design and build scalable data pipelines on GCP using BigQuery and Apache Spark for a data and AI company.
Freelance Data Engineer
Design and build cloud-based data pipelines and infrastructure for an agritech project, ensuring scalable ingestion, storage, and analytics for IoT and other data sources.