Data Engineer (contract)

Description Title: Data Engineer Location: Irving, TX Duration: 12 months Work Engagement: W2 Work Schedule: Onsite Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits Summary: In this contingent resource assignment, you may: Consult on or participate in moderately complex initiatives and deliverables within Information Security Engineering and contribute to large-scale planning related to Information Security Engineering deliverables. Review and analyze moderately complex Information Security Engineering challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Information Security Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Information Security Engineering. Required Qualifications: Information Security Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education. Key Requirements: • Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship. • Strong understanding of Google Cloud architecture, including bucket structuring, naming standards, lifecycle management policies, and access control mechanisms. • Hands-on experience working with columnar data formats such as Parquet, Avro, and ORC, along with associated compression strategies. • Experience building both batch and streaming ingestion pipelines using GCP-native services. • Knowledge of Pub/Sub–based streaming architectures, including event schema design, schema evolution, and versioning best practices. • Familiarity with incremental ingestion techniques and Change Data Capture (CDC) patterns. • Understanding of data consumption and exposure patterns including views, APIs, and curated analytical datasets.