A Data Engineer is responsible for designing, developing, and managing the company's data infrastructure and systems. They collaborate with cross-functional teams to gather data requirements, design and implement data models, and ensure data integrity and availability. The ideal candidate should have a strong background in data engineering, ETL processes, and database management.

1. Design, develop, and maintain data pipelines and ETL processes to transform and load data into the company's data warehouse.
2. Collaborate with data scientists and analysts to understand data requirements, and implement data models and schemas.
3. Optimize data infrastructure and systems for scalability and performance.
4. Ensure data quality and integrity by implementing data validation and cleansing processes.
5. Manage and monitor databases, ensuring availability and security.
6. Develop and maintain documentation for data infrastructure and systems.
7. Stay up-to-date with the latest trends and technologies in data engineering.
8. Train and mentor junior data engineers.

Preferred Candidate:

1. Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
2. Minimum 8 years of experience in data engineering or a related role.
3. Strong knowledge of data engineering concepts and best practices.
4. Experience with ETL tools and frameworks (e.g., Apache Spark, Apache Beam, Talend).
5. Proficient in SQL and database management systems (e.g., PostgreSQL, MySQL, Oracle).
6. Experience with cloud-based data technologies (e.g., AWS Redshift, Google BigQuery, Azure Data Lake).
7. Strong programming skills in Python, Java, or Scala.
8. Experience with data modeling and schema design.
9. Knowledge of data warehousing concepts and architectures.
10. Experience with version control systems (e.g., Git).