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)

#J-18808-Ljbffr

📌 AWS data Engineering (Centro)
🏢 Brillio
📍 Centro