Overview
A continuación se detalla todo lo que necesita saber sobre lo que implica esta oportunidad, así como lo que se espera de los solicitantes.
As a Data Integration & Data Warehousing Engineer, you will design and run scalable data pipelines and enterprise data warehouses in a cloud-enabled environment to fuel analytics and decision-making. You’ll collaborate with global teams to ensure data quality, governance, and performance across the organization. The role supports Schneider Digital’s mission to drive digital transformation, enabling sustainable outcomes through data. You will work with AWS, Informatica, and modern data tooling to deliver reliable datasets and scalable solutions.
Compensaciones / Ventajas
flexible schedule and hybrid work
vacation and personal time policies (Holy Pack, floating holidays)
global family leave policy
Wellbeing programs (Wellwo, Wellhub)
life insurance and flexible remuneration plan
Stock ownership program
Responsabilidades
Design, develop, and maintain scalable data pipelines using Python, AWS Glue, and Informatica PowerCenter
Create robust ETL/ELT workflows to ingest data from databases, APIs, files, and SaaS systems




Build reusable ingestion frameworks for on-prem to cloud data migrations
Develop and maintain dimensional models and optimize data structures for analytics
Develop and manage AWS Glue jobs with PySpark/Python; orchestrate workflows across AWS (Redshift, Lambda)
Monitor ETL pipelines, troubleshoot data issues, and implement logging and alerting
Perform data profiling, reverse engineering, and ad-hoc analysis; deliver clean, reliable datasets
Support downstream systems with optimized data delivery and performance
Requisitos principales
Bachelor’s or Master’s degree in xqbhyrx Engineering, Computer Science, or related field
Typically 5 years of experience in data engineering, ETL, or data warehousing
Strong hands-on experience in Python / PySpark
Proficiency in SQL and data modeling for analytics
Experience building and maintaining data pipelines (ETL/ELT)
Experience with AWS services (AWS Glue, AWS Lambda, S3)
Version control using GIT
Strong analytical and problem-solving abilities
Attention to data quality and accuracy
Strong collaboration across cross-functional teams
Python
PySpark
SQL

📌 Senior, Data Engineer (Barcelona)
🏢 Schneider Electric
📍 Barcelona