> Markdown version of [/jobs/ext/4291195-data-engineer-ii-google-cloud-platform-google-cloud-platform-ai](https://www.wearedevelopers.com/jobs/ext/4291195-data-engineer-ii-google-cloud-platform-google-cloud-platform-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer II Google Cloud Platform (Google Cloud Platform) & AI

- **Company:** HTC Global Services, Inc.
- **Location:** Dearborn, MI, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Business Analytics Applications, BigQuery, Cloud Engineering, Code Generation, Information Engineering, Data Fusion, Data Infrastructure, Data Transformation, Data Systems, Data Warehousing, Software Debugging, Programming Tools, Cloud Services, Software Engineering, SQL Stored Procedures, Systems Integration, Unstructured Data, Data Processing, Google Cloud, Data Ingestion, GitHub Copilot, Large Language Models, Multi-Agent Systems, Agentic-AI, Data Lakes, AI Platforms, Google Cloud Functions, Data Analytics, Qlikview, Google Gemini
- **Published:** October 26, 2026
- **Apply:** https://www.dice.com/job-detail/bd98c1b7-7396-462a-bc7e-80cf9bb7bea1

## About the Role

We are seeking a Data Engineer II with 4+ years of data engineering experience to design, build, and maintain scalable data infrastructure, pipelines, and platforms. The ideal candidate will have experience with Google Cloud Platform (Google Cloud Platform), data ingestion and transformation, data modeling, data warehousing, and AI-assisted development tools., * 4+ years of professional data engineering experience.

 * Experience with Google Cloud Platform (Google Cloud Platform) services, including cloud-native application development and deployment.
 * Strong knowledge of data modeling, data warehousing, and data analytics.
 * Experience with data ingestion, data wrangling, data transformation, and loading data into BigQuery.
 * Experience with stored procedures, triggers, data modeling, QlikView, Cloud Functions, Data Fusion, Astronomer, and Apache Airflow.
 * Intermediate-level AI skills.
 * Strong understanding of AI-assisted development tools, such as Gemini Code Assist, OpenCode, and GitHub Copilot.
 * Knowledge of agentic AI concepts, including AI agents, autonomous workflows, multi-agent systems, and LLM-based automation.
 * Experience integrating AI tools into the software development lifecycle, including code generation, debugging, testing, and documentation.
 * Bachelor's or master's degree.

Preferred Qualifications

 * Experience with Google Cloud Platform cloud services and cloud-native application development and deployment.
 * Familiarity with Google Cloud Platform AI services, including Vertex AI, Gemini models, and AI APIs.

## Description

* Collaborate with business and technology stakeholders to understand current and future data requirements.
 * Design, build, and maintain reliable, efficient, and scalable data infrastructure for data collection, storage, transformation, and analysis.
 * Develop and maintain data pipelines, data models, and applications to support efficient and reliable data workflows.
 * Design, implement, and maintain data platforms, including data warehouses, data lakes, and data lakehouses, for structured and unstructured data.
 * Develop analytical tools, algorithms, and programs to support data engineering activities.
 * Write scripts and automate tasks to improve operational efficiency.
 * Ensure optimal performance of data solutions and identify opportunities for improvement.
 * Perform data ingestion, data wrangling, and data transformation, including loading data into BigQuery.
 * Work with stored procedures, triggers, data modeling, QlikView, Cloud Functions, Data Fusion, Astronomer, and Apache Airflow.
 * Leverage AI-assisted development tools to improve developer productivity across coding, debugging, testing, and documentation.
 * Apply knowledge of agentic AI concepts, AI agents, autonomous workflows, multi-agent systems, and large language models (LLMs) to support software development and business process automation.