Data Engineer

Job Descriptions:

• Design and implement key components for highly scalable, distributed, fault-tolerant data collection and analysis system built for handling data on a large scale
• Build out scalable and reliable ETL or ELT pipelines and processes to ingest data from a large number and variety of data sources
• Maintain and optimize the performance of data analytics infrastructure to ensure accurate, reliable, and timely delivery of key insights for decision making
• Streamline data access and security to enable data scientists and analysts to easily access data whenever they need to
• Support other teams by guiding data usage, processing, and how they can best leverage the platform you are building
• Create and maintain Machine Learning pipelines that are scalable, robust, and ready for production.

Requirements:

• Have a degree or higher in Computer Science, Software Engineering, Information Technology or other related technical disciplines.
• 3-5 years of relevant work experience, especially in building data infrastructure from scratch (from raw data source to analysis-ready data)
• Analytical, data-driven, reliable, and results-oriented.
• Having strong skill & knowledge in ETL tools, database design, data APIs, algorithms and data structure.
• Successful track-record of database systems (SQL & NoSQL), cloud data warehousing solutions & data architecture knowledge.
• Know programming language such as Python, Scala, etc (nice to have).
• Familiarity with Google Cloud Platform and its Analytics Stack (BigQuery, Compute Engine, Cloud SQL, Cloud Storage, Networking).
• Familiarity with workflow orchestration like Airflow, DagSter, Prefect, etc.
• Knowledge in Data Science Project is big plus.
• An agile trait.