Data Engineer

Deskripsi pekerjaan Data Engineer PT Avows Technologies

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or related field.
• 2–4+ years of experience in data and software engineering, with strong hands-on experience in .NET/C#.
• Experience building and maintaining data pipelines, ETL/ELT processes, and data integration solutions.
• Strong knowledge of C# and .NET Core/.NET 6+.
• Experience working with SQL databases such as SQL Server, PostgreSQL, or MySQL.
• Familiarity with ETL/data integration tools and data processing frameworks.
• Understanding of Data Warehouse concepts, including fact tables, dimension tables, ETL, and data modeling.
• Experience developing REST APIs and integrating data from various systems is a plus.
• Familiarity with cloud platforms such as Microsoft Azure, AWS, or GCP.
• Understanding of database performance optimization, query tuning, indexing, and data quality.
• Familiarity with Git, CI/CD, Docker, and Agile/Scrum methodologies.
• Strong analytical and problem-solving skills.
• Able to collaborate with software engineers, data analysts, and other technical teams.

Responsibilites

• Design, develop, and maintain data pipelines and ETL/ELT processes to collect, transform, and integrate data from various sources.
• Develop and maintain data processing applications and backend services using C#/.NET.
• Build and maintain REST APIs and data integration services to support data exchange between internal and external systems.
• Develop, optimize, and maintain SQL queries, stored procedures, views, and database objects.
• Design and implement scalable data models and data warehouse solutions according to business requirements.
• Integrate data from relational databases, APIs, applications, files, and other data sources.
• Monitor data pipelines and applications, troubleshoot failures, and ensure data accuracy, reliability, and availability.
• Perform data transformation, cleansing, validation, and quality checks to ensure consistency across systems.
• Optimize application and database performance, including query optimization, indexing, and resource utilization.
• Develop reusable and maintainable .NET-based components and data services following software engineering best practices.
• Implement automated testing, version control, and CI/CD pipelines for data and application deployments.
• Support cloud-based data solutions and services, particularly within the Microsoft Azure ecosystem.
• Maintain technical documentation for data pipelines, APIs, database structures, and integration processes.