Prada Data Engineer

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Location
MilanLombardyItaly
Seniority
Mid-Level
Department
IT & Technology Systems
Industry
Fashion, Apparel & Leather Goods
Posted
May 14, 2026

About Prada

A leading luxury house within the global luxury goods sector, operating at the intersection of artisanal heritage and modern retail technology. The employer combines a rigorous commitment to craftsmanship with group-level investments in digital platforms and data capabilities to support omnichannel commerce and personalized client experiences.

Data Engineer at a leading luxury house in Milan, Italy — responsible for building scalable data platforms and pipelines to support analytics and commerce.

Role & Responsibilities

  • Design, build and maintain scalable data pipelines (ETL/ELT) to consolidate transactional, e‑commerce and CRM datasets for analytics and downstream consumers.
  • Implement and optimise data models and data warehouses/lakes to support reporting, BI and machine learning use cases.
  • Integrate and orchestrate streaming and batch data sources using best‑practice frameworks to ensure low‑latency, reliable data delivery.
  • Ensure data quality, lineage and governance by implementing validation, monitoring and remediation processes in line with regulatory requirements (e.g., GDPR).
  • Collaborate with data scientists, product owners, BI teams and business stakeholders to translate requirements into technical solutions and operational SLAs.
  • Deploy and maintain data infrastructure in cloud or hybrid environments, including automation, CI/CD and observability for production systems.
  • Document architectures, runbooks and onboarding materials; mentor junior engineers and contribute to platform standards and roadmap.

Qualifications

  • Proven track record designing and operating production data pipelines and data platforms.
  • Strong proficiency in SQL and at least one programming language for data engineering (Python, Scala or Java).
  • Experience with distributed processing frameworks (e.g., Apache Spark) and workflow orchestration tools (e.g., Apache Airflow).
  • Practical knowledge of cloud data services (AWS, GCP or Azure) and modern data warehouse technologies (Snowflake, BigQuery or Redshift).
  • Familiarity with stream-processing tools (e.g., Kafka) and containerisation/orchestration (Docker, Kubernetes).
  • Solid understanding of data modelling, data governance, and privacy/compliance obligations in an EU context.
  • Effective communicator able to liaise with technical and non-technical stakeholders across functions.

Skills

SQL Python Apache Spark Apache Airflow Apache Kafka Snowflake BigQuery Amazon Redshift AWS GCP Azure Docker Kubernetes dbt Git Linux

Experience

Typically 3–5 years of professional experience in data engineering, cloud data platforms or a closely related field, with demonstrable ownership of end‑to‑end production data systems.

Education

Bachelor's degree in Computer Science, Engineering, Data Science or a related quantitative discipline; equivalent professional experience considered.

Workplace

This position is based in Milan, Lombardy, Italy.

Culture

The organisation values precision, discretion and an entrepreneurial approach to digital transformation. Teams operate in a fast‑paced, collaborative environment that balances respect for heritage and design excellence with the delivery of scalable, data‑driven solutions.

About Cerulean

Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.

Frequently Asked Questions

A.

The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Prada, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Data Platform Engineer», «ETL Engineer», «Analytics Engineer», «Data Infrastructure Engineer», «Big Data Engineer», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.