Senior Data Engineer – GCP

ZipStaff•Freeport, ME

10h•Remote

About The Position

ZipStaff is seeking an experienced Data Engineer to implement and support data ingestion and pipeline processes on Google Cloud Platform for a major retail organization. The role involves designing, developing, configuring, testing, debugging, and documenting processes ranging from simple to complex, based on business requirements and technical architecture specifications. The engineer will also support and troubleshoot existing ingestion and pipeline processes, helping ensure they are reliable, scalable, and aligned with business and technical standards. The position is remote, with the Freeport, Maine area preferred, and is a W2 contract through ZipStaff; C2C and 1099 arrangements are not accepted.

Requirements

At least 5 years of experience as a Data Engineer or in a similar role focused on data ingestion, pipelines, and ETL/ELT processes.
Hands-on experience implementing data ingestion and pipeline processes on Google Cloud Platform.
Ability to design, develop, configure, test, debug, and document data processes based on business requirements and technical architecture specifications.
Experience supporting and troubleshooting existing data ingestion and pipeline processes.
Familiarity with industry-standard best practices for data engineering on cloud platforms.
Ability to work remotely.

Nice To Haves

Prior experience building and maintaining data pipelines in a retail or e-commerce environment.
Background with GCP data services such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, or related tools.
Experience with data quality, monitoring, and operational support of production pipelines.
Hands-on experience translating technical architecture specifications into production-ready data solutions.

Responsibilities

Implement simple to complex data ingestion and pipeline processes on Google Cloud Platform using industry-standard best practices.
Design, develop, configure, test, debug, and document data processes based on business requirements and technical architecture specifications.
Support and troubleshoot existing data ingestion and pipeline processes and related data flows.
Ensure data pipelines are reliable, scalable, and aligned with business and technical standards.
Collaborate with stakeholders to translate requirements into effective data engineering solutions.
Document processes, configurations, and technical details to support ongoing operations and knowledge sharing.