Data Engineer II

Guadalajara - Mexico

Monthly Salary: Not Disclosed

Posted on: 14 hours ago

Vacancies: 1 Vacancy

Job Summary

Purpose Statement: The Data Engineer II designs builds and maintains robust and scalable data pipelines and infrastructure to support the organizations data needs particularly related to cloud-based technologies. This includes acquiring transforming and optimizing large datasets to ensure high-quality reliable and accessible data for analytics reporting machine learning and AI initiatives.

Key Job Accountabilities:

Lead Data Pipeline and Infrastructure Development: Design develop and optimize end-to-end ETL/ELT pipelines(on-premises and cloud) using Python SQL Spark etc. to ingest data into scalable cloud infrastructure including Data Lakes and Data Warehouses (AWS Azure or GCP).
Collaborate on data modeling and schema design: Collaborate with stakeholders to design and implement efficient data models and schema structures. Enforce data quality through robust validation monitoring and alerting mechanisms to ensure accuracy and reliability.
Optimize Performance Cost and Scalability: Proactively evaluate tune and improve the performance scalability and cost-efficiency of all data pipelines and underlying cloud infrastructure.
Enforce Best Practices and Documentation: Champion and enforce modern data engineering best practices including version control automated testing and CI/CD. Create and maintain comprehensive technical documentation for all data systems and operational procedures.
Mentorship: Provide technical guidance mentorship and perform code reviews for junior team members actively fostering a culture of continuous learning and high standards within the data engineering team.
All GT team members are responsible for upholding the organizations cybersecurity posture by adhering to security policies and procedures actively participating in training protecting data and systems actively identifying and mitigating vulnerabilities and promptly reporting any suspicious activity or potential security incidents.

Education/Experience Qualifications:

Bachelors Degree with 5 or more years of related experience is preferred. An equivalent combination of education and/or experience will be considered .

Other Qualifications:

Proven experience with cloud data platforms (e.g. AWS S3 Redshift Glue; Azure Data Lake Synapse Data Factory; Google Cloud Storage BigQuery Dataflow).
Strong proficiency in SQL and at least one programming language (e.g. Python Java Scala) for data manipulation scripting.
Experience with big data technologies (e.g. Spark Hadoop) is a plus.
Familiarity with data governance data security and compliance principles.
Excellent problem-solving analytical and communications skills.

This document does not represent a contract of employment and is not intended to capture every possible assignment the incumbent could be asked to perform.

Required Experience:

Purpose Statement: The Data Engineer II designs builds and maintains robust and scalable data pipelines and infrastructure to support the organizations data needs particularly related to cloud-based technologies. This includes acquiring transforming and optimizing large datasets to ensure high-quali...

Key Job Accountabilities:

Lead Data Pipeline and Infrastructure Development: Design develop and optimize end-to-end ETL/ELT pipelines(on-premises and cloud) using Python SQL Spark etc. to ingest data into scalable cloud infrastructure including Data Lakes and Data Warehouses (AWS Azure or GCP).
Collaborate on data modeling and schema design: Collaborate with stakeholders to design and implement efficient data models and schema structures. Enforce data quality through robust validation monitoring and alerting mechanisms to ensure accuracy and reliability.
Optimize Performance Cost and Scalability: Proactively evaluate tune and improve the performance scalability and cost-efficiency of all data pipelines and underlying cloud infrastructure.
Enforce Best Practices and Documentation: Champion and enforce modern data engineering best practices including version control automated testing and CI/CD. Create and maintain comprehensive technical documentation for all data systems and operational procedures.
Mentorship: Provide technical guidance mentorship and perform code reviews for junior team members actively fostering a culture of continuous learning and high standards within the data engineering team.
All GT team members are responsible for upholding the organizations cybersecurity posture by adhering to security policies and procedures actively participating in training protecting data and systems actively identifying and mitigating vulnerabilities and promptly reporting any suspicious activity or potential security incidents.

Education/Experience Qualifications:

Bachelors Degree with 5 or more years of related experience is preferred. An equivalent combination of education and/or experience will be considered .

Other Qualifications:

Proven experience with cloud data platforms (e.g. AWS S3 Redshift Glue; Azure Data Lake Synapse Data Factory; Google Cloud Storage BigQuery Dataflow).
Strong proficiency in SQL and at least one programming language (e.g. Python Java Scala) for data manipulation scripting.
Experience with big data technologies (e.g. Spark Hadoop) is a plus.
Familiarity with data governance data security and compliance principles.
Excellent problem-solving analytical and communications skills.

This document does not represent a contract of employment and is not intended to capture every possible assignment the incumbent could be asked to perform.

Required Experience:

Key Skills

Apache Hive
S3
Hadoop
Redshift
Spark
AWS
Apache Pig
NoSQL
Big Data
Data Warehouse
Kafka
Scala

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