US_East | Data Engineer_L2

Client is seeking a GCP Data Engineer with hands-on experience with Google Cloud Platform (GCP) services, particularly BigQuery, and be proficient in DBT (Data Build Tool) for data transformation and modeling. This role requires strong SQL skills, a solid understanding of data warehousing concepts, and light proficiency in Python for scripting and automation.

Position Title: Data Engineer - GCP
Location: New York, NY (Onsite)
Duration: Long Term Contract
 
Job description:
Client is seeking a GCP Data Engineer with hands-on experience with Google Cloud Platform (GCP) services, particularly BigQuery, and be proficient in DBT (Data Build Tool) for data transformation and modeling. This role requires strong SQL skills, a solid understanding of data warehousing concepts, and light proficiency in Python for scripting and automation. Have understanding of CES and call transcript data.
 
Basic Qualifications:

• Immediate availability
• Mandatory background check

 
Required Skills:

• Hands-on experience with Google Cloud Platform (GCP) services, particularly BigQuery
• Proficient in DBT (Data Build Tool) for data transformation and modeling
• Strong SQL skills
• Solid understanding of data warehousing concepts
• Light proficiency in Python for scripting and automation
• Understanding of CES and call transcript data

 
Preferred Qualifications:

• Experience in designing and maintaining scalable data pipelines
• Knowledge of data governance, security, and compliance standards

 
Role and responsibilities:

• Design, build, and maintain scalable data pipelines on GCP, primarily using BigQuery
• Develop and manage DBT models to transform raw data into clean, tested, and documented datasets
• Write complex and optimized SQL queries for data extraction, transformation, and analysis
• Implement and maintain data warehousing solutions, ensuring performance, scalability, and reliability
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions
• Monitor and troubleshoot data pipeline performance and data quality issues
• Automate data workflows and tasks using Python scripts where necessary
• Ensure data governance, security, and compliance standards are met