What are the responsibilities and job description for the GCP Data Engineer with Python position at Saransh Inc?
Role: GCP Data Engineer with Python
Location: Dearborn, MI (4 days a week onsite)
Job Type: Contract
Experience: Overall 8 to 12 years
Job Summary
Location: Dearborn, MI (4 days a week onsite)
Job Type: Contract
Experience: Overall 8 to 12 years
Job Summary
- The Data Engineer will be responsible for supporting the Credit Global Securitization (GS) team’s upskilling initiative by contributing to data engineering efforts across cloud and traditional platforms.
- This role is intended to accelerate development and delivery.
- The engineer will work closely with cross-functional teams to build, optimize, and maintain data pipelines and workflows using GCP, Python, and ETL tools.
- Minimum 3 years of hands-on experience with Google Cloud Platform (GCP), specifically using Astronomer/Composer for orchestration.
- Strong proficiency in Python for data engineering and automation.
- Experience with RDBMS technologies such as DB2 and Teradata.
- Exposure to Big Data ecosystems and distributed data processing.
- Prior experience with ETL tools like DataStage or Informatica.
- The Data Engineer will play a key role in the developing and maintaining scalable data pipelines and workflows.
- The engineer will work with GCP tools like Astronomer/Composer and leverage Python for automation and transformation tasks.
- The role involves integrating data from RDBMS platforms such as DB2 and Teradata, and supporting ETL processes using tools like DataStage or Informatica.
- The engineer will collaborate with existing team members, including Software Analysts and Scrum Masters, and will be expected to contribute to knowledge sharing and process improvement.
- Develop and implement solutions using GCP, Python, Big Data technologies to enhance data analysis capabilities.
- Collaborate with cross-functional teams to design and optimize data models in Teradata and DB2 environments.
- Utilize Python for scripting and automation to streamline geospatial data processing tasks.
- Integrate and manage data workflows using Cloud Composer to ensure efficient data pipeline operations.
- Leverage GCP Cloud to deploy scalable applications and services.