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)

📌 AWS data Engineer (Redshift, Aurora, Glue, Lambda, Step Functions) (Centro)
🏢 Brillio
📍 Centro