Data Platform Engineer

Summary: As a Data Platform Engineer, you will spend your day supporting the development and design of the data platform architecture. Your role involves working closely with various architects to ensure seamless integration of systems and data models. You will engage in collaborative efforts to align platform components and contribute to the overall data strategy, ensuring that the platform meets organizational needs efficiently and effectively. Roles & Responsibilities: - Serve as a subject matter expert (SME) for AWS Glue-based data integration and ETL solutions. - Design, develop, maintain, and optimize ETL/ELT pipelines using AWS Glue, Python, PySpark, and other AWS data services. - Develop reusable frameworks, utilities, and automation solutions to improve data engineering efficiency and reliability. - Troubleshoot and resolve complex data processing, performance, and integration issues across multiple environments. - Monitor, tune, and optimize data pipelines to meet performance, scalability, and cost-efficiency requirements. - Work with AWS services such as S3, Glue Data Catalog, Lambda, IAM, CloudWatch, Step Functions, and Redshift to build end-to-end data solutions. - Support CI/CD implementation, code reviews, testing, and deployment activities for data engineering solutions. Professional & Technical Skills: - Required Skill: AWS Glue, Python, and PySpark for large-scale data processing. - Experience working with AWS services including S3, Lambda, IAM, CloudWatch, Step Functions, and Redshift. - Strong knowledge of SQL and relational databases. - Experience designing and implementing data pipelines, data lakes, and data warehousing solutions. - Understanding of data modeling, data quality frameworks, and data governance principles. - Experience with source control, CI/CD pipelines, and Agile development methodologies. - Strong analytical, problem-solving, and communication skills. - Ability to work independently while collaborating effectively with multiple teams and stakeholders. Additional Information: - More than 3 years of hands-on experience in data engineering, ETL development, or cloud-based data integration. - This position is based at our Manila office. Minimum 2 year(s) of experience is required

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