Overview

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 / Beneficios adaptable 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 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