Key Responsibilities: ETL Solutions: Design, implement, and manage scalable ETL solutions using the AWS technology stack, including EventBridge, Lambda, Glue, Step Functions, Redshift, and CloudWatch. Data Pipeline Management: Develop, enhance, debug, and maintain data pipelines for seamless operations and high performance. Best Practices: Implement best practices to ensure data availability, computational efficiency, cost optimization, and data quality within Snowflake and AWS environments. Process Enhancement: Build and improve data products, tools, and functionalities to support data lake implementation and advanced analytics, including prototypes and production systems. Production Support: Provide ongoing support for production data pipelines to ensure reliability and performance. Issue Resolution: Monitor, troubleshoot, and promptly resolve issues in data pipelines and ETL processes. Automation: Create scripts and tools to automate routine tasks and enhance system efficiency. Compliance: Ensure all data operations adhere to organizational policies and regulatory requirements. Required Qualifications: Bachelors degree in Computer Science, Engineering, or a related IT field. Experience: 45 years in software development. 3+ years of hands-on experience with AWS ETL solutions, including EventBridge, Lambda, Glue, Step Functions, Redshift, and CloudWatch. Technical Skills: Proficiency in SQL, S3, AWS Glue, PySpark, Python, Lambda, Redshift (Columnar DB), AWS IAM, Step Functions, Git, Terraform, and CI/CD pipelines. Additional Skills: Exposure to the MSBI stack (SSIS, SSAS, and SSRS) is a plus. Preferred Qualifications: Comprehensive knowledge of AWS Data Services. Advanced coding skills in Python and PySpark. Hands-on experience with SSIS for ETL design and implementation. Cloud Data Analytics or Engineering certifications.
