Top Data Engineer Jobs in Milan

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.

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 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.

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.

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.

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 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.

As a Senior Data Engineer, you'll build and manage data pipelines, ensure data quality, and collaborate across teams, contributing to the Data Platform's growth.

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.

Design and develop cloud-native backend services in Rust to process terabytes of data daily. Build and operate data-intensive microservices on AWS and Kubernetes, integrate with distributed databases and messaging systems (Kafka/RabbitMQ), and collaborate across teams to deliver observability features.

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 Senior Data Engineer will lead the design and evolution of scalable data architectures, mentor team members, build data pipelines, and integrate Generative AI into workflows.

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.

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.

As a Founding Data and ML Engineer, you will design scalable data pipelines, develop AI/ML models, and enhance product performance through applied AI techniques.

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.

Design, develop, and deploy production-grade ML and AI solutions including LLM fine-tuning, RAG architectures, NLP pipelines, time-series forecasting, supplier risk and anomaly detection, scalable data pipelines, and RESTful integrations with enterprise systems.

Design and develop a big-data processing engine and heavy ETL pipelines (including geo-location analysis) across cloud and on-prem. Build distributed, partitioned pipeline architectures using Spark/PySpark, Scala, Airflow, Kubernetes, and cloud platforms; follow Agile, clean-code, and software design best practices while supporting deployments and client-facing interactions.

Design and maintain scalable data pipelines and platforms, lead migration from Snowflake to client service, propose improvements, drive initiatives, and collaborate with senior engineers, product/project managers, and data analysts.