Trách nhiệm
Collaborate with Data Analysts and Business Teams to understand data needs and provide timely solutions for reporting and insights.
Work on data integration from various sources, including APIs, web services, and databases.
Utilize tools such as AWS QuickSight, Grafana, and Google Sheets for data visualization to support business decision-making.
Support developing and maintaining scalable data pipelines and ETL/ELT processes to collect, clean, and process large-scale datasets in data systems.
Monitor data pipeline performance and troubleshoot issues to ensure data integrity and availability.
Document technical processes, contribute to data catalogs, and ensure compliance with data governance policies.
Engage in continuous learning and improvement, staying updated with industry best practices in Data Engineering.
Work on data integration from various sources, including APIs, web services, and databases.
Utilize tools such as AWS QuickSight, Grafana, and Google Sheets for data visualization to support business decision-making.
Support developing and maintaining scalable data pipelines and ETL/ELT processes to collect, clean, and process large-scale datasets in data systems.
Monitor data pipeline performance and troubleshoot issues to ensure data integrity and availability.
Document technical processes, contribute to data catalogs, and ensure compliance with data governance policies.
Engage in continuous learning and improvement, staying updated with industry best practices in Data Engineering.
Yêu cầu
Bachelor's degree in Computer Science, Information Systems Management or related fields.
2+ years of experience in data engineering, ETL development, or a similar role.
Proficiency in using advanced SQL queries to extract valuable insights from datasets.
Experience in one of the following programming languages: Python or C# for data processing and scripting.
Experience with relational databases, such as PostgreSQL, MySQL, Oracle, or MS SQL Server.
Understanding of cloud computing platforms (e.g., AWS, GCP, Azure).
Excellent problem-solving skills, attention to detail, and the ability to work independently or as part of a team.
Strong communication and collaboration skills, particularly in an Agile environment.
Proficient in English, with the ability to communicate, read, and write effectively in a professional work environment.
Preferred (but not required)
Experience working with BI tools such as AWS QuickSight, Grafana, or Google Sheets.
Familiarity with data orchestration tools like Airflow or dbt.
Exposure to cloud-based storage solutions and data lake architecture.
Familiarity with the Agile toolset, such as GitLab, Jira, Confluence, and Slack.
2+ years of experience in data engineering, ETL development, or a similar role.
Proficiency in using advanced SQL queries to extract valuable insights from datasets.
Experience in one of the following programming languages: Python or C# for data processing and scripting.
Experience with relational databases, such as PostgreSQL, MySQL, Oracle, or MS SQL Server.
Understanding of cloud computing platforms (e.g., AWS, GCP, Azure).
Excellent problem-solving skills, attention to detail, and the ability to work independently or as part of a team.
Strong communication and collaboration skills, particularly in an Agile environment.
Proficient in English, with the ability to communicate, read, and write effectively in a professional work environment.
Preferred (but not required)
Experience working with BI tools such as AWS QuickSight, Grafana, or Google Sheets.
Familiarity with data orchestration tools like Airflow or dbt.
Exposure to cloud-based storage solutions and data lake architecture.
Familiarity with the Agile toolset, such as GitLab, Jira, Confluence, and Slack.
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