Data Engineer Infrastructure  

Job Responsibilities:

- Design, develop, and maintain robust data platform infrastructure, databases, and data pipelines to ensure high performance and scalability.

- Design, develop, and maintain Extract, Transform, Load (ETL) processes to facilitate data movement and transformation across various systems.

- Ensure data availability, reliability, and scalability through best practices in data engineering and infrastructure management.

- Collaborate with other teams, including software engineering, data science, and product management, to integrate and optimize data systems.

- Build and maintain efficient, scalable, and stable data pipelines for large-scale data processing.

- Understand the evolving needs and challenges of platform users and develop strong tools and platform features to address these needs.

Job Requirements:

- 1-2 years of experience in data engineering or software development with a focus on data infrastructure.

- Proficiency in Java, Scala, and Python.

- Experience with version control systems like Git and build tools like Maven.

- Containerization and orchestration tools such as Docker and Kubernetes.

- Experience with big data technologies such as Apache Flink, Kafka, Flume, Spark, and Apache Airflow.

- Hands-on experience with relational and non-relational databases such as MySQL and MongoDB.

- Experience in handling big data and data warehousing in cloud environments.

- Strong problem-solving skills and the ability to manage multiple tasks and projects simultaneously.

- Excellent communication and teamwork skills, with the ability to work collaboratively in a cross-functional environment.

- Eagerness to learn new technologies and continuously improve technical skills.

- Familiarity with DevOps practices and automation tools is preferable.