GCP Data Engineer

Job Title: GCP Data Engineer Duration (Contract): 4 Months Client Location: Denver, CO Location Preference: Onsite Job Description As a GCP Data Engineer, you will design and develop cloud-based data solutions that support analytics, business intelligence, and AI-driven initiatives. You will build scalable data marts, develop automated data pipelines, integrate third-party APIs, and maintain enterprise analytical datasets within the Google Cloud Platform ecosystem. Key Responsibilities Design and develop scalable data marts and analytical data products in Google Cloud Platform. Build automated data pipelines integrating third-party APIs and enterprise data sources. Develop Python-based solutions for data extraction, transformation, automation, and API integrations. Write and optimize complex SQL queries for data transformation, validation, and analytics. Integrate digital marketing, business, and external data sources into unified reporting models. Implement data quality, monitoring, validation, logging, and reconciliation processes. Maintain and enhance existing marketing and analytics data marts. Create data models that support reporting, business intelligence, analytics, and AI use cases. Develop technical documentation covering data flows, architecture, business rules, and support procedures. Collaborate with analytics, engineering, architecture, and production support teams to deploy and maintain solutions. Required Skills, Experiences, Education, and Competencies Strong experience in Data Engineering, Analytics Engineering, or Software Engineering roles. Advanced SQL expertise with the ability to develop complex queries from scratch. Proficiency in Python for API development, automation, data integration, and transformation. Hands‑on experience building data pipelines, ETL processes, and analytical data models. Experience integrating data from REST APIs and third‑party platforms. Strong experience with Google Cloud Platform and cloud‑based data services. Knowledge of dimensional modeling, data warehousing, data grain, and reusable analytical datasets. Experience implementing data quality controls, monitoring, exception handling, and validation processes. Experience with source control, collaborative development practices, and technical documentation. Experience with dbt, dlt, DuckDB, Adobe Analytics, AI/LLM‑powered solutions, BI tools (Tableau, Looker, Power BI), GitHub, Jira, and regulated industry environments preferred. The hourly range for roles of this nature are $40.00 to $80.00/hr. Rates are heavily dependent on skills, experience, location, and industry. cyberThink is an Equal Opportunity Employer. #J-18808-Ljbffr Smart IMS