Ingeniero De Datos Aws

The Big Jobsite; Aguascalientes; On-site; MXN 900,000 - 1,600,000; Full time

Job summary

Capgemini Mexico is seeking a Senior Data Engineer (AWS) to design, build and evolve enterprise-scale data platforms. You will develop scalable data pipelines, optimize data lakes and warehouses, and collaborate with cross-functional teams on end-to-end cloud data solutions.

In this role, you will promote governance, quality, automation and security, while contributing to modern data architectures and cost-efficient cloud practices across multiple business domains.

Qualifications

• Experience designing data lakes and data warehouses on AWS.
• Proficient in Python, SQL and Spark for ETL/ELT pipelines.
• Knowledge of data governance, security and cost optimization on cloud.

Responsibilities

• Design and implement scalable Data Lake and Data Warehouse architectures on AWS.
• Develop and maintain robust ETL/ELT pipelines using Python, SQL, Spark and AWS services.
• Integrate data from multiple sources including APIs, databases, files and enterprise apps.
• Optimize data processing workflows for performance, scalability, reliability and cost efficiency.
• Implement data quality, governance, lineage and security controls across the data ecosystem.
• Develop and support cloud-native data solutions using AWS Glue, Lambda, Redshift, EMR, Athena, S3.
• Automate ingestion, transformation, monitoring and deployment with DevOps/CI-CD practices.
• Collaborate with architects, analysts, data scientists and engineers to deliver data solutions.
• Troubleshoot data integration and platform issues while driving continuous improvement.

Skills

AWS data engineering

ETL/ELT development

Cloud-native architectures

Data lake design

Python

SQL

Spark

AWS services

Tools

AWS Glue

AWS Lambda

Amazon Redshift

AWS EMR

Amazon Athena

Amazon S3

Job description

Senior Data Engineer (AWS) Capgemini Mexico

As a Senior Data Engineer, you will play a key role in designing, building, and evolving enterprise-scale data platforms that enable data-driven decision-making and advanced analytics. Leveraging deep expertise in AWS and modern data engineering practices, you will develop scalable, secure, and high-performance data solutions that support business‑critical initiatives. In this role, you will contribute to architecture decisions, design robust data pipelines, optimize data platforms, and collaborate with multidisciplinary teams to deliver end-to-end data solutions. You will help shape modern data ecosystems while promoting best practices in governance, quality, automation, and cloud engineering.

Your Role Responsibilities & Scope

• Design and implement scalable Data Lake and Data Warehouse architectures on AWS.


• Develop and maintain robust ETL/ELT pipelines using Python, SQL, Spark, and AWS services.


• Integrate data from multiple sources including APIs, databases, files, and enterprise applications.


• Optimize data processing workflows for performance, scalability, reliability, and cost efficiency.


• Implement data quality, governance, lineage, and security controls across the data ecosystem.


• Develop and support cloud-native data solutions using AWS Glue, Lambda, Redshift, EMR, Athena, S3, and related services.


• Automate ingestion, transformation, monitoring, and deployment processes using DevOps and CI/CD practices.


• Collaborate with architects, analysts, data scientists, and engineering teams to deliver business-focused data solutions.


• Troubleshoot complex data integration and platform challenges while driving continuous improvement initiatives.


• Contribute to technical strategy, architecture reviews, and data platform modernization efforts.

Your Profile

• Demonstrates strong expertise in AWS data engineering, ETL/ELT development, cloud-native architectures, and large-scale data platform design, delivering secure and scalable solutions.


• Applies a data-driven and problem-solving mindset, proactively identifying optimization opportunities and transforming complex business requirements into effective data solutions.


• Collaborates effectively with architects, data scientists, analysts, and engineering teams, fostering alignment, knowledge sharing, and successful project outcomes.


• Takes ownership of data quality, governance, security, automation, and operational excellence, ensuring trusted and reliable data assets across the enterprise.


• Embraces innovation, continuous learning, and modern engineering practices, leveraging emerging technologies and cloud capabilities to accelerate business value and digital transformation.

What you’ll love

• Join global employee networks that promote engagement, development, and belonging.


• Access continuous learning through internal academies, certifications, and mentorship.


• Well-being hub and different wellbeing initiatives

Need to know Flexible Schedules: We support flexible working hours to accommodate different lifestyles, time zones, and family responsibilities. Career Development in Spanish & English: Training, certifications, and mentorship programs available in both languages to support bilingual growth.

About Capgemini

Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of over 420,000 team members in more than 50 countries. We deliver end-to end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. At Capgemini Mexico, we aim to attract the best talent and are committed tocreating a diverse and inclusive work environment, so there is nodiscrimination based on race, sex, sexual orientation, gender identity orexpression, or any other characteristic of a person. All applications welcomeand will be considered based on merit against the job and/or experience for the position.