Senior Tech Specialist, Cloud Engineering - R01573478

Mexico·GuadalajaraEmployeesenior

EngineeringDevops Engineer

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Quick Summary

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.

Requirements Summary

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.

Technical Tools

EngineeringDevops Engineer

Senior Data Engineer

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

AWS Data EngineerIng Advanced: Data Engineer

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.