【Responsibilities】
1. Create and maintain optimal data pipeline architecture, assemble large and complex datasets to meet functional/nonfunctional business requirements.
2. Build the infrastructure required for optimal extraction, transformation, and loading data from a wide variety of data sources.
3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for greater scalability, etc.
4. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
5. Work with data and analytics experts to strive for greater functionality in our data systems.
6. Support cross functional, cross BU data integration tasks.

【Requirements】
1. 3+ years of data and software engineering experience and at least two completed project life cycle.
2. 3+ years of experience with data modeling, data warehousing, and building ETL pipelines.
3. Programming experience with manipulating and analyzing data (e.g. Python, Shell, SQL).
4. Experience with at least one SQL/NoSQL databases (e.g. MySQL, PostgreSQL, Mongo).
5. Experience with workflow management tools (e.g. Airflow, Dagster, Nifi).
6. Experience with backend API development (e.g. Django, Flask, FastAPI).
7. Experience with containerized application development (e.g. Docker, Kubernetes).
8. Experience with Google Cloud Platform Service (e.g. BigQuery, CloudSQL, PubSub).
9. Strong knowledge of message queue (e.g. Kafka, RabbitMQ).
10. Basic knowledge of Linux operating system.

【Pluses】
1. Basic knowledge of Machine Learning algorithm.
2. Experience with deploying and scaling Machine Learning models.
3. Experience with Golang development and GraphQL implementation.
4. Experience with first line or second line system operation and maintenance.
　

more info>>>https://ikala.tv