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

2. Implement and maintain robust database architectures, ensuring effective data modeling, normalization, and query optimization for large-scale analytics platforms

3. Write, review, and optimize complex SQL queries for 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, Lambda, Step Functions, and EventBridge

2. Amazon S3, Redshift, and Aurora

3. Database design, data modeling, and normalization techniques

4. Complex SQL query development and optimization

5. Python programming for data engineering, ETL development, and automation

6. Building and maintaining scalable data pipelines on AWS

7. Data warehousing concepts and performance tuning

8. AWS CloudWatch for monitoring and alerting

9. Amazon DynamoDB and Amazon Kinesis for data streaming and storage

Preferred Skills

1. AWS analytics services such as Athena, EMR, and OpenSearch

2. Infrastructure-as-code tools like CloudFormation

3. Amazon SNS and SQS for messaging and event-driven architectures

4. AWS security tools such as Macie

5. Spark (Scala) and big data processing frameworks

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)

📌 AWS data Engineering (Guadalajara)
🏢 Brillio
📍 Guadalajara