Remote ETL Data Engineer — Build Global Data Pipelines

BairesDev

Región Centro

Remote

MXN 1,829,000 - 2,561,000

Full time

14 days+
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Benefits offered by this job

100% remote
USD or local currency compensation
Hardware and software setup for remote
Flexible hours
Parental leave & holidays
Multicultural environment
Mentorship and growth opportunities

Job summary

BairesDev is seeking an ETL + Data Engineer to join our globally distributed, 100% remote Development team. You will tackle diverse projects with a multicultural team and help design, build, and optimize ETL solutions and data pipelines that power our products and clients worldwide.

You will work with AWS, Lambda, and other cloud technologies to deliver scalable data platforms, while collaborating with architects and developers to achieve robust data architectures and reliable data flows.

Qualifications

  • 5+ years of experience as ETL and/or Data Engineer, with strong data skills.
  • Good understanding of cloud technologies and data pipelines.
  • Experience with Lambda functions and AWS ecosystem is desirable.

Responsibilities

  • Develop complex SQL queries and analyze data; integrate systems and data warehouses.
  • Design and maintain ETL solutions; optimize data flows.
  • Collaborate with developers, tech leads, and solution architects to build applications.
  • Improve existing ETL processes to meet business requirements.
  • Contribute to data architecture decisions and implementation plans.

Skills

ETL/Data Engineer
Cloud technologies
Data pipeline
Lambda functions
Advanced English

Tools

AWS
Terraform

Job description

BairesDev is seeking an ETL + Data Engineer to join our globally distributed, 100% remote Development team. You will tackle diverse projects with a multicultural team and help design, build, and optimize ETL solutions and data pipelines that power our products and clients worldwide.

You will work with AWS, Lambda, and other cloud technologies to deliver scalable data platforms, while collaborating with architects and developers to achieve robust data architectures and reliable data flows.

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