AWS data Engineering

Brillio; Región Centro; On-site; MXN 420,000 - 860,000; Full time

Job summary

Brillio is seeking an experienced AWS Data Engineer in Mexico to design and optimize scalable data pipelines and ETL workflows using Glue, Lambda, Step Functions and Redshift. The role requires 4–7 years of hands-on experience with cloud-based data architectures, SQL, Python, and data warehousing best practices.

You will ensure high data quality, performance, and reliability while collaborating with cross-functional teams.

Qualifications

• Hands-on experience architecting and building cloud-based data pipelines in AWS.
• Proficient in SQL query development, data modeling, and normalization for analytics.
• Experience with ETL development, data ingestion, and automation using Python.
• Strong troubleshooting, performance tuning, and incident response in cloud environments.

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

Skills

Data pipeline design

SQL query optimization

Python programming

Cloud data engineering

Collaboration

Education

Bachelor's degree in Computer Science or related field

AWS Data Analytics Certification or AWS Solutions Architect – Associate

Python programming certification (e.g., PCAP)

Tools

AWS Glue

AWS Lambda

AWS Step Functions

AWS EventBridge

Amazon S3

Amazon Redshift

Amazon Aurora

CloudWatch

DynamoDB

Kinesis

Job description

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)