Deskripsi Pekerjaan
Are you a passionate Data Engineer looking to elevate your career within a dynamic, global environment? RiDiK, a subsidiary of CLPS (Nasdaq: CLPS), is seeking a Mid-Level or Senior Data Engineer to join our high-performing team. In this role, you will be instrumental in designing, building, and maintaining enterprise-scale data pipelines that drive critical business intelligence and analytical insights.
We operate in an Agile, fast-paced environment where innovation is encouraged. You will work closely with cross-functional teams to modernize our data stack, leveraging cutting-edge cloud technologies to solve complex data challenges. If you thrive on optimizing data workflows, ensuring data integrity, and delivering scalable solutions, this is the perfect opportunity to make a tangible impact.
Tanggung Jawab
- Design, develop, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from diverse sources.
- Collaborate with stakeholders to translate business requirements into efficient data models.
- Optimize data warehouse performance in Snowflake to ensure fast query response times and cost-efficiency.
- Implement modular data transformations using dbt to ensure maintainable and testable data architecture.
- Monitor and troubleshoot data integration issues, ensuring high availability and data quality across all pipelines.
- Participate in Agile ceremonies, providing technical estimates and contributing to sprint planning.
- Mentor junior team members and conduct code reviews to uphold engineering best practices.
Kualifikasi
- Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field.
- 3+ years of professional experience in data engineering or related data-focused roles.
- Proficiency in SQL is mandatory, with advanced knowledge of complex query optimization.
- Hands-on experience with modern cloud data warehouses, specifically Snowflake.
- Expertise in Python for data manipulation and automation.
- Experience with dbt (data build tool) for managing complex data transformations.
- Strong understanding of data architecture patterns (e.g., Star Schema, Data Vault).
- Familiarity with CI/CD pipelines and version control systems like Git.