Direct message the job poster from hyqoo sr. sourcing specialist @ hyqoo (formerly cliksource) | mba, technical recruiting job title: data operations engineer location: remote (colombia) experience level: entry to mid-level (3-5) introduction: we are seeking a highly skilled and detail-oriented data operations engineer to join our growing data platform team. in this role, you will play a crucial part in designing, building, and optimizing data infrastructure that supports our next-generation products and data-driven decision-making. you will develop scalable, secure, and high-performance data pipelines while ensuring effective integration with cloud platforms, big data tools, and ci/cd automation frameworks. the ideal candidate is technically strong, has hands-on experience with aws, big data processing, and automation, and can collaborate with cross-functional teams with ease. roles and responsibilities: 1. data pipeline building and optimization: - build and maintain scalable data pipeline architecture using spark and orchestration tools like airflow or aws step functions. - manage large, complex datasets to meet business and performance needs. - identify, design, and implement process improvements to automate data ingestion, transformation, and loading. - enhance reliability through pipeline monitoring, failure detection, and automated recovery. - leverage snowflake and dbt for optimized data warehousing and transformation workflows. 2. data platform and self-serving infrastructure: - design and implement robust infrastructure using aws services such as em...
Direct message the job poster from hyqoo sr. sourcing specialist @ hyqoo (formerly clik source) | mba, technical recruiting job title: data operations engineer location: remote (colombia) experience level: entry to mid-level (3-5) introduction: we are seeking a highly skilled and detail-oriented data operations engineer to join our growing data platform team. in this role, you will play a crucial part in designing, building, and optimizing data infrastructure that supports our next-generation products and data-driven decision-making. you will develop scalable, secure, and high-performance data pipelines while ensuring effective integration with cloud platforms, big data tools, and ci/cd automation frameworks. the ideal candidate is technically strong, has hands-on experience with aws, big data processing, and automation, and can collaborate with cross-functional teams with ease. roles and responsibilities: 1. data pipeline building and optimization: - build and maintain scalable data pipeline architecture using spark and orchestration tools like airflow or aws step functions. - manage large, complex datasets to meet business and performance needs. - identify, design, and implement process improvements to automate data ingestion, transformation, and loading. - enhance reliability through pipeline monitoring, failure detection, and automated recovery. - leverage snowflake and dbt for optimized data warehousing and transformation workflows. 1. data platform and self-serving infrastructure: - design and implement robust infrastructure using aws services such as em...
Direct message the job poster from hyqoo sr. sourcing specialist @ hyqoo (formerly clik source) | mba, technical recruiting job title: data operations engineer location: remote (colombia) experience level: entry to mid-level (3-5) introduction: we are seeking a highly skilled and detail-oriented data operations engineer to join our growing data platform team. in this role, you will play a crucial part in designing, building, and optimizing data infrastructure that supports our next-generation products and data-driven decision-making. you will develop scalable, secure, and high-performance data pipelines while ensuring effective integration with cloud platforms, big data tools, and ci/cd automation frameworks. the ideal candidate is technically strong, has hands-on experience with aws, big data processing, and automation, and can collaborate with cross-functional teams with ease. roles and responsibilities: 1. data pipeline building and optimization: - build and maintain scalable data pipeline architecture using spark and orchestration tools like airflow or aws step functions. - manage large, complex datasets to meet business and performance needs. - identify, design, and implement process improvements to automate data ingestion, transformation, and loading. - enhance reliability through pipeline monitoring, failure detection, and automated recovery. - leverage snowflake and dbt for optimized data warehousing and transformation workflows. 2. data platform and self-serving infrastructure: - design and implement robust infrastructure...
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