Data Engineer (Python, Spark, AWS, Iceberg, Airflow, DBT, Snowflake)
Position Overview:
We are looking for a talented Big Data Engineer to join our dynamic team immediately. The ideal candidate will have a strong background in big data technologies and a passion for building scalable data frameworks. You will play a crucial role in developing a configuration-driven framework utilizing Python and Spark, driving the success of our data initiatives.
Key Responsibilities:
Design and implement a configuration-driven framework using Python and Spark.
Collaborate with cross-functional teams to understand data requirements and ensure data quality and integrity.
Work with AWS services, including EMR, to efficiently process and analyze large datasets.
Utilize tools such as Airflow and DBT for workflow orchestration and data transformation.
Develop, test, and maintain scalable data pipelines and ETL processes.
Ensure version control and collaboration through GIT.
Optimize existing processes and identify opportunities for improvements in data processing and analytics.
Monitor and troubleshoot data pipelines to ensure reliable data delivery.
Mandatory Skills:
Proficient in Python and Spark.
Experience with AWS services, particularly EMR.
Familiarity with Iceberg, GIT, Airflow, DBT, Trino, Snowflake, and Linux/Unix environments.
Strong problem-solving skills and the ability to work in a fast-paced environment.
Qualifications:
Bachelor’s degree in Computer Science, Data Science, or a related field.
Proven experience as a Big Data Engineer or in a similar role.
Strong understanding of big data technologies and methodologies.
Are you available to start new position immediately?
Are you familiar with Python, Spark, AWS Services with EMR, Iceberg, GIT, Airflow, DBT, Trino, Snowflake, DBT, Linux/Unix and Airflow. ? These are the mandatory skills.
Are you available to work full-time (8 AM ~ 5 PM PST) remotely at your home?