AWS data Engineer (Redshift, Aurora, Glue, Lambda, Step Functions)

Brillio; Región Centro; Presencial; MXN 600.000 - 900.000; Jornada completa

Descripción de la vacante

Brillio is seeking an experienced Data Engineer to design, build, and optimize scalable AWS data pipelines and ETL workflows using Glue, Lambda, Step Functions, Redshift, and S3.

You will model data, write complex SQL, and develop Python automation for ingestion and transformation. The role includes monitoring, troubleshooting, and collaborating with support teams to ensure reliable real-time and batch processing.

Formación

• 4–7 years of experience in AWS data engineering and cloud-based data pipeline development.
• Experience designing scalable data pipelines and ETL workflows on AWS.
• Strong SQL development and optimization for large-scale analytics.
• Proficient in Python for data ingestion, transformation, and automation.
• Experience with real-time and batch data processing on AWS.

Responsabilidades

• Design, develop, and optimize scalable data pipelines and ETL workflows on AWS.
• Implement robust data architectures with modeling and normalization.
• Write and optimize complex SQL queries for data extraction and transformation.
• Develop Python automation scripts for data ingestion and cloud-native apps.
• Monitor and troubleshoot cloud-based data workflows for high availability.
• Collaborate with support teams to analyze data-related Hypercare tickets.
• Integrate AWS services like S3, EventBridge, and Aurora for real-time/batch processing.
• Contribute to data warehousing best practices and performance tuning.

Conocimientos

AWS Glue, Lambda, Step Functions, and

S3, Redshift, and Aurora

Database design, modeling, and normal.

Complex SQL query development

Python for data engineering

Data pipelines on AWS

Data warehousing concepts

AWS CloudWatch monitoring

DynamoDB and Kinesis streaming

Educación

Bachelor's degree in Computer Science / IT / Data Engineering

AWS Certified Data Analytics – Specialty or AWS Solutions Architect – Associate

Python/data engineering certification (PCAP)

Herramientas

CloudFormation

Spark (Scala)

OpenSearch

Athena

EMR

DynamoDB

Kinesis

Descripción del empleo

Experience Range: 4 to 7 years of experience, including hands-on AWS data engineering and cloud-based data pipeline development

Key Responsibilities:

• Design, develop, and optimize scalable data pipelines and ETL workflows using AWS services such as Glue, Lambda, Step Functions, and Redshift
• Implement and maintain robust database architectures, ensuring effective data modeling, normalization, and query optimization for large-scale analytics platforms
• Write, review, and optimize complex SQL queries for data extraction, transformation, and loading across multiple AWS data stores
• Develop automation scripts and data engineering solutions using Python to streamline data ingestion, transformation, and cloud-native application processes
• Monitor, troubleshoot, and resolve technical issues in cloud-based data workflows, ensuring high availability and reliability of data services
• Collaborate with application support teams to resolve Hypercare tickets, providing technical guidance and root cause analysis for data-related issues
• Integrate AWS services such as S3, EventBridge, and Aurora to support real-time and batch data processing requirements
• Enhance data processing performance by implementing best practices in data warehousing and contributing to system performance tuning initiatives

Required Skills:

• AWS Glue, Lambda, Step Functions, and EventBridge
• Amazon S3, Redshift, and Aurora
• Database design, data modeling, and normalization techniques
• Complex SQL query development and optimization
• Python programming for data engineering, ETL development, and automation
• Building and maintaining scalable data pipelines on AWS
• Data warehousing concepts and performance tuning
• AWS CloudWatch for monitoring and alerting
• Amazon DynamoDB and Amazon Kinesis for data streaming and storage

Preferred Skills:

• AWS analytics services such as Athena, EMR, and OpenSearch
• Infrastructure-as-code tools like CloudFormation
• Amazon SNS and SQS for messaging and event-driven architectures
• AWS security tools such as Macie
• Spark (Scala) and big data processing frameworks

Desired Qualifications:

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline
• AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Associate certification
• Certification in Python programming or data engineering (such as Python Institute PCAP or equivalent)