Data Engineer su Google Cloud Platform
Pubblicato il 13-09-2026 - Target Reply in Italia
Join Us: Data Engineering to Unlock Value from Data (Milano-Torino)
question = "Are you a Data Lover? "
print("Target Reply is your place.")
Are you passionate about building data platforms and enabling AI-driven solutions ?
At Target Reply, you design and develop data systems that turn raw data into actionable insights and power advanced analytics and Artificial Intelligence.
Target Reply is a consulting company specialized in Analytics, Big Data, Data Science, Cloud Architectures, and Artificial Intelligence. Target Reply's main goal is simple: get value from data. Working at Target Reply means sitting at the table with tier-one customers across several industries, playing a first-level game. You will design and implement solutions based on modern data architectures and emerging technologies: Cloud-Native solutions, Real-Time Processing, Big Data, Artificial Intelligence, Machine Learning — that's our bread and butter.
You design and implement end-to-end data pipelines, from ingestion to consumption.
You contribute to building scalable data platforms that support analytics and AI use cases.
Technologies: You work with Big Data frameworks, distributed storage systems, and cloud-native services (AWS, Azure, GCP). You use Python, Scala, or Java and integrate data solutions with AI/ML workflows.
AI integration: You enable AI-driven use cases by preparing, transforming, and serving data for Machine Learning models, real-time analytics, and intelligent applications.
You collaborate in cross-functional teams, contributing to architectural decisions and ensuring high-quality delivery in complex environments.
A degree in Computer Science, Engineering, Mathematics, Statistics, or other data-related fields.
Valuable expertise
• Knowledge or familiarity of data engineering and Big Data ecosystems
• Hands-on experience with Spark, Kafka, Java, Pyhton or Scala
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Understanding of data modeling, data pipelines, and dist