Senior Tech Specialist, Cloud Engineering - R01573478

Brillio; Región Centro; On-site; MXN 900,000 - 1,300,000; Full time

Job summary

Brillio is hiring a Senior Data Engineer in Mexico to design and optimize scalable data pipelines using AWS services, including Glue, Lambda, and Redshift. You will build robust data models, write complex SQL, and develop Python-driven ingestion workflows for analytics at scale.

The role emphasizes real-time and batch processing with S3, EventBridge, and Aurora, plus performance tuning of data warehouses. 2–4 years of hands-on AWS data engineering experience is preferred.

Qualifications

• 2–4 years of hands-on AWS data engineering experience.

Responsibilities

• Design, develop, and optimize scalable data pipelines and ETL workflows using AWS services (Glue, Lambda, Step Functions, Redshift).
• Implement and maintain robust database architectures with data modeling and query optimization.
• Write, review, and optimize complex SQL queries for data extraction and loading across AWS stores.
• Develop Python-based data ingestion, transformation, and automation workflows.
• Monitor, troubleshoot, and ensure high availability of cloud-based data pipelines.
• Collaborate with application support teams to resolve Hypercare tickets and provide data guidance.
• Integrate S3, EventBridge, and Aurora for real-time and batch processing.
• Improve data processing performance through warehousing best practices.

Skills

Athena

SNS

SQS

CloudWatch

Macie

Spark

Scala

Kinesis

CloudFormation

EMR

Open Search

DynamoDB

Amazon API Gateway

SCT

Redshift

DMS

Oozie

Education

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline

Tools

AWS Glue

AWS Lambda

AWS Step Functions

Amazon EventBridge

Amazon S3

Amazon Redshift

Amazon Aurora

Database design and data modeling

Complex SQL query development

Python programming for data engineering and ETL automation

AWS CloudWatch

Data warehousing concepts and performance tuning

AWS Athena

AWS EMR

AWS OpenSearch

CloudFormation

Amazon SNS

Amazon SQS

AWS Macie

Spark

Scala

Amazon DynamoDB

Amazon Kinesis

Job description

Senior Data Engineer

Primary Skills

• Athena, SNS, SQS, CloudWatch, Macie, Spark - Scala, Kinesis, CloudFormation, EMR, Open Search, DynamoDB, Amazon API Gateway, SCT, Redshift, DMS, Oozie

Specialization

• AWS Data EngineerIng Advanced: Data Engineer

Job requirements

• Experience Range: With at least 2 to 4 years of hands-on AWS data engineering experience, including cloud-based data pipeline development. Key Responsibilities: 1. Design, develop, and optimize scalable data pipelines and ETL workflows using AWS services such as Glue, Lambda, Step Functions, and Redshift to support business analytics. 2. Implement and maintain robust database architectures, ensuring effective data modeling, normalization, and query optimization for high-volume analytics platforms. 3. Write, review, and optimize complex SQL queries for efficient data extraction, transformation, and loading across multiple AWS data stores. 4. Develop automation scripts and data engineering solutions using Python to streamline data ingestion, transformation, and cloud-native application processes. 5. Monitor, troubleshoot, and resolve technical issues in cloud-based data workflows, ensuring high availability and reliability of data services. 6. Collaborate with application support teams to resolve Hypercare tickets, providing technical guidance and root cause analysis for data-related issues. 7. Integrate AWS services such as S3, EventBridge, and Aurora to support real-time and batch data processing requirements. 8. Enhance data processing performance by implementing best practices in data warehousing and contributing to system performance tuning initiatives. Required Skills: 1. AWS Glue 2. AWS Lambda 3. AWS Step Functions 4. Amazon EventBridge 5. Amazon S3 6. Amazon Redshift 7. Amazon Aurora 8. Database design and data modeling 9. Complex SQL query development 10. Python programming for data engineering and ETL automation 11. AWS CloudWatch for monitoring and alerting 12. Data warehousing concepts and performance tuning Preferred Skills: 1. AWS Athena 2. AWS EMR 3. AWS OpenSearch 4. Infrastructure-as-code tools such as CloudFormation 5. Amazon SNS and SQS for messaging and event-driven architectures 6. AWS Macie for data security 7. Spark (Scala) and big data processing frameworks 8. Amazon DynamoDB and Amazon Kinesis for data streaming and storage Desired Qualifications: 1. Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline 2. AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Associate certification 3. Certification in Python programming or data engineering such as Python Institute PCAP or equivalent Additional Information: Application support, management, and development responsibilities; strong technical knowledge required. Resolve Hypercare tickets as part of ongoing support.