Mexico-based Senior ETL Engineer: PySpark & Teradata

Turtle Trax S.A.

Región Centro

Presencial

MXN 784.381 - 1.132.996

Jornada completa

14 días+

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Descripción de la vacante

Turtle Trax S.A. is seeking an ETL Developer based in Mexico, Jalisco. The role involves designing and developing ETL workflows using tools like Ab Initio, Informatica PowerCenter, or IBM DataStage. Candidates should have expertise in SQL, data warehouses, and experience with Teradata and PySpark.

The ideal candidate will have at least 5 years in ETL/Data Engineering, and a Bachelor's degree in a relevant field. Strong collaboration skills are essential for working with business analysts and stakeholders to ensure efficient data processes.

Formación

  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
  • 5+ years of experience in ETL/Data Engineering development.
  • Strong analytical, problem-solving, and troubleshooting skills.

Responsabilidades

  • Design, develop, test, and deploy ETL workflows using Ab Initio, Informatica PowerCenter, or IBM DataStage.
  • Develop and optimize complex SQL queries and stored procedures.
  • Build and maintain data integration processes for enterprise data warehouses.

Conocimientos

ETL tool experience
SQL development
Teradata databases
PySpark
Unix/Linux shell scripting
Data validation

Educación

Bachelor's degree in Computer Science or related field

Herramientas

Ab Initio
Informatica PowerCenter
IBM DataStage

Descripción del empleo

Turtle Trax S.A. is seeking an ETL Developer based in Mexico, Jalisco. The role involves designing and developing ETL workflows using tools like Ab Initio, Informatica PowerCenter, or IBM DataStage. Candidates should have expertise in SQL, data warehouses, and experience with Teradata and PySpark.

The ideal candidate will have at least 5 years in ETL/Data Engineering, and a Bachelor's degree in a relevant field. Strong collaboration skills are essential for working with business analysts and stakeholders to ensure efficient data processes.

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