Data Engineer I

Amazon; Pisa; In loco; EUR 35.000 - 55.000; Tempo pieno

Descrizione del lavoro

A leading e-commerce company located in Tuscany, Italy, is seeking a Data Engineer I to build and scale data ingestion pipelines. The role requires 1+ years of data engineering experience, proficiency in data modeling, and familiarity with ETL processes. Responsibilities include developing data pipelines using Spark and AWS services and ensuring data consistency across various sources. This position also involves creating APIs that integrate AI insights with business tools and monitoring the health of the data pipelines.

Competenze

• 1+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with one or more query language (e.g., SQL, PL/SQL).
• Experience with one or more scripting language (e.g., Python).

Mansioni

• Build batch and streaming data pipelines using Spark and AWS services.
• Implement automated checks to ensure data consistency.
• Define and maintain data contracts with source teams.
• Develop cross-domain metadata services linking data catalogs.
• Create APIs and event-driven workflows for AI insights.
• Monitor pipeline health and costs.

Conoscenze

Data engineering experience

Data modeling

ETL pipelines

SQL or similar query language

Python or scripting language

Strumenti

Spark

AWS (including Lambda, S3, SageMaker)

Big data technologies (Hadoop, Hive)

ETL tools (Informatica, SSIS)

Descrizione del lavoro

Fulfillment by Amazon (FBA) enables sellers to scale their businesses globally by leveraging Amazon’s world‑class fulfillment network. Sellers using FBA benefit from fast, reliable shipping, Prime delivery eligibility, and hassle‑free returns—allowing them to focus on growth while we handle operations.

The WW FBA Central Analytics team builds and operates scalable, enterprise‑grade data infrastructure, tools, and analytics solutions that power WW FBA business. We partner across global product, program, and operations teams to unify diverse datasets, deliver self‑service analytics, and develop next‑generation capabilities using LLMs to unlock insights.

Our charter includes building the foundational pipelines, governance frameworks, and intelligent interfaces that enable internal customers to query, analyze, and act on complex datasets with natural language. This is an opportunity to work on one of the largest, complex, and critical analytics ecosystems, designing solutions that combine massive scale, high reliability, and advanced AI.

We are seeking a Data Engineer I who will support a GenAI‑powered insights assistant initiative by building and scaling ingestion and embedding pipelines for unstructured WW FBA knowledge bases. Your role ensures the retrieval‑augmented generation system accesses fresh, relevant document embeddings to enhance AI‑driven insights and user query satisfaction.

Key job responsibilities

• Build batch and streaming data pipelines using Spark and AWS streaming services.
• Implement automated checks to ensure data consistency across different data types.
• Define and maintain data contracts with source teams to keep schemas consistent.
• Develop cross‑domain metadata services linking structured and unstructured data catalogs.
• Create APIs and event‑driven workflows integrating AI insights with business tools.
• Monitor pipeline health, costs, and SLA adherence.

Basic Qualifications

• 1+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).
• Experience with one or more scripting language (e.g., Python, KornShell).

Preferred Qualifications

• Experience with big data technologies such as Hadoop, Hive, Spark, EMR.
• Experience with any ETL tool like Informatica, ODI, SSIS, BODI, Datastage, etc.
• Familiarity with RAG (Retrieval‑Augmented Generation) principles.
• AWS experience: Lambda, S3, SageMaker, Bedrock Knowledge Bases.

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