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.