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# Data Engineer (Google Cloud Platform & AI)

- **Company:** Everforth Apex
- **Location:** Dearborn, MI, United States
- **Experience:** Experienced
- **Salary:** $104,000.0 - $145,600.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Business Analytics Applications, Big Data, BigQuery, Cloud Engineering, Code Generation, Information Engineering, Data Infrastructure, Data Systems, Data Warehousing, Software Debugging, Cloud Data Fusion, Software Engineering, SQL Stored Procedures, Systems Integration, Unstructured Data, Workflow Management Systems, Data Processing, Google Cloud, Data Ingestion, GitHub Copilot, Large Language Models, Multi-Agent Systems, Agentic-AI, Data Lakes, Qlikview, Google Gemini, Data Pipelines
- **Published:** October 20, 2026
- **Apply:** https://www.dice.com/job-detail/9310ed11-1385-426e-93de-42dac35eb79c

## About the Role

The ideal candidate will have strong hands-on experience with Google Cloud Platform (Google Cloud Platform), BigQuery, data pipelines, data modeling, and data warehousing, along with practical knowledge of AI-assisted development tools and Agentic AI concepts., * Bachelor's or Master's degree.

 * 4+ years of professional Data Engineering experience.
 * Strong experience with:
 + Data engineering and analytics
 + Data modeling
 + Data warehousing
 + Data ingestion and transformation
 + Google Cloud Platform
 + BigQuery
 * Experience with Google Cloud Platform services and cloud-native application development and deployment.
 * Working knowledge of AI-assisted development tools, such as:
 + Gemini Code Assist
 + GitHub Copilot
 + OpenCode
 * Mid-level knowledge of AI and Agentic AI concepts, including AI agents, autonomous workflows, multi-agent systems, and LLM-based solutions.
 * Experience integrating AI tools into software development workflows, including code generation, debugging, testing, or documentation.

Preferred Qualifications

 * Experience with Google Cloud Platform Cloud Functions.
 * Experience with Cloud Data Fusion.
 * Experience with Apache Airflow and/or Astronomer.
 * Experience developing stored procedures and triggers.
 * Experience with QlikView.
 * Familiarity with Vertex AI, Gemini models, and other Google Cloud Platform AI APIs/services.

## Description

We are seeking a Data Engineer II to design, build, and maintain scalable data solutions and infrastructure that support the collection, storage, transformation, processing, and analysis of large volumes of data., * Collaborate with business and technology stakeholders to understand current and future data requirements.

 * Design, build, and maintain reliable, efficient, and scalable data infrastructure.
 * Develop and maintain data pipelines, data models, and applications supporting efficient and reliable data workflows.
 * Build solutions for data ingestion, transformation, and data wrangling, including loading data into BigQuery.
 * Design, implement, and maintain modern data platforms, including data warehouses, data lakes, and lakehouse architectures, supporting structured and unstructured data.
 * Develop analytical tools, scripts, algorithms, and automation to support data engineering processes.
 * Develop and maintain stored procedures and triggers supporting data processing requirements.
 * Work with Google Cloud Platform technologies and services, including Cloud Functions and Cloud Data Fusion.
 * Support workflow orchestration using Apache Airflow and Astronomer.
 * Work with QlikView and other data and analytics technologies as needed.
 * Monitor and optimize data solutions for performance, reliability, scalability, and efficiency.
 * Incorporate AI-assisted development tools, including Gemini Code Assist, OpenCode, and GitHub Copilot, into development workflows.
 * Apply AI capabilities to activities such as code generation, debugging, testing, documentation, and developer productivity.
 * Develop an understanding of and work with Agentic AI concepts, including AI agents, autonomous workflows, multi-agent systems, and large language models (LLMs).
 * Leverage or support Google Cloud Platform AI capabilities such as Vertex AI, Gemini models, and AI APIs, where applicable.