29 Data Engineer jobs in Italy available for remote work from home. Apply for positions such as Data Engineer, Data Engineer, Data Engineer (Senior) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Data Engineer will design and maintain robust ETL/ELT pipelines on GCP while optimizing data infrastructure for scalability. They will also build analytics tools and integrate diverse data ecosystems to provide actionable insights for business performance.
Design and implement modern data platforms, including Data Mesh and Lambda/Kappa architectures, to transform data into valuable insights. Responsibilities include developing scalable AI ecosystems and ensuring data quality and governance across on-premises and cloud environments.
You will design and maintain a central data ecosystem to provide a unified 360-degree view of customers across 60+ brands. This involves building scalable ETL/ELT pipelines and establishing robust data governance frameworks to support business intelligence and AI initiatives.
You will be responsible for operating and extending cloud infrastructure for data ingestion pipelines to support model training. You will also collaborate with scientists and leadership to define the dataset roadmap and improve data quality and cost-efficiency.
Lead the RTS delivery squad and oversee the end-to-end architecture and delivery of strategic, API-driven data products. Mentor engineering team members while establishing technical standards, CI/CD practices, and robust data quality monitoring.
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You will own the full lifecycle of data products, collaborating with Data Scientists to bring real-time pricing algorithms to production. Additionally, you will architect data pipelines, manage infrastructure, and lead cross-team efforts to scale machine learning solutions.
Design, build, and maintain scalable data solutions and ETL/ELT workflows using Microsoft Fabric. Collaborate with cross-functional teams to support analytics and business intelligence through reliable data platforms.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for AI products.
The role involves managing data collection and ingestion pipelines to support large-scale model training operations. You will collaborate with scientists and leadership to optimize data infrastructure and define the dataset roadmap for AI products.
You will own the full lifecycle of data products, collaborating with Data Scientists to bring real-time pricing algorithms to production. You will also architect data pipelines, manage infrastructure, and lead cross-team efforts to scale ML development and deployment.
The intern will develop practical skills in database modeling, optimization, and data analysis while supporting data quality initiatives. They will work alongside experienced professionals on real-world projects to transform information into business insights.
You will own the end-to-end tracking and reporting of computer vision accuracy metrics while curating and labeling datasets to improve model performance. Additionally, you will build and maintain continuous learning pipelines to ensure models are retrained and deployed efficiently.
You will be responsible for harmonizing customer data across systems and managing data pipelines to ensure consistency and accuracy. Additionally, you will collaborate with marketing and product teams to optimize customer engagement strategies using platforms like Braze.
You will design and scale robust data architectures while owning end-to-end data pipelines to ensure data trustworthiness. Additionally, you will lead architectural decisions and build production-grade data services to support Finance and Operations teams.
The Senior Data Engineer will design, develop, and optimize complex data pipelines and integration processes while ensuring data quality and monitoring. They will also collaborate with multidisciplinary teams and stakeholders, providing technical mentoring to junior staff.
Design and maintain data architectures to ensure compliance with global privacy regulations using OneTrust. Automate DSAR workflows and integrate privacy tools with internal data sources like DynamoDB and S3.
Perform day-to-day operational and DevOps tasks to maintain Wikimedia's public-facing infrastructure. Lead continuous improvement through automation and collaborate with product teams on scalable architectural designs.
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Design and optimize Snowflake data models and pipelines to power CRM, personalization, and audience activation. Collaborate with cross-functional teams to build customer 360 views and ensure data quality and scalability.
Design, build, and optimize scalable data pipelines to transform raw data into actionable insights. Lead the evolution of data infrastructure while ensuring high performance and reliability across cloud environments.
Design and implement scalable data systems in collaboration with client teams and vendors. Manage and optimize data flows using an Agile methodology.
Build and maintain resilient streaming and batch data pipelines to ingest, normalize, and distribute market and trading data. Develop self-serve tooling and data governance frameworks to ensure high-quality, observable, and performant data products across the organization.
You will define the architecture for the data platform and lead the design of scalable, low-latency pipelines for high-volume payment transactions. Additionally, you will mentor senior engineers and partner with cross-functional teams to ensure data reliability and business value.
You will design and maintain a central data ecosystem to provide a unified source of truth across 60+ global sub-brands. This involves building scalable ETL/ELT pipelines and establishing robust data governance frameworks to support business intelligence and AI initiatives.
Lead the design and implementation of scalable data pipeline architectures while defining engineering standards and platform best practices. Act as the primary technical reference for client stakeholders and mentor team members to ensure high-quality delivery of data engineering programs.
You will build and maintain data pipelines and reporting services to support a global merchant base. Additionally, you will contribute to the development of a new self-service Reporting API and participate in on-call rotations for production incidents.
You will develop and maintain efficient data pipelines while collaborating with cross-functional teams to meet data objectives. Additionally, you will utilize Python and AI to optimize data infrastructure and ensure high standards of data quality and security.
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Perform startup and commissioning of modular data center equipment while conducting on-site technical diagnostics and root cause analysis. Document test results, produce site reports, and provide operational training to customers.
Lead and grow a small senior data engineering team while acting as a player-coach to evolve the data architecture. Own the end-to-end data lifecycle including ingestion, transformation via dbt, and the delivery of self-service BI tools.
Define and drive the technical roadmap for a team of engineers while overseeing architectural decisions and implementation. Foster a culture of continuous learning and professional growth to ensure high-impact delivery of scalable solutions.
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