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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Google Cloud Platform Data Engineer - **Company:** Stefanini - **Location:** United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Business Analytics Applications, Data Analysis, Big Data, Cloud Engineering, Code Generation, Information Engineering, Data Fusion, Data Infrastructure, Data Systems, Data Warehousing, Software Debugging, Programming Tools, Software Engineering, SQL Stored Procedures, Data Processing, Scripting, Google Cloud, Cloud Platform System, Data Ingestion, GitHub Copilot, Large Language Models, Multi-Agent Systems, Data Lakes, AI Platforms, Google Cloud Functions, Qlikview, Data Management, Virtual Agents, Data Pipelines - **Published:** July 29, 2026 - **Apply:** https://www.dice.com/job-detail/c944c5ca-6ccd-42a4-80c2-65ce33b5730a ## About the Role Key ResponsibilitiesCollaborate 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.Plan, design, build, and maintain scalable data solutions, including data pipelines, data models, and applications, for efficient and reliable data workflows.Design, implement, and maintain existing and future data platforms, including data warehouses, data lakes, and data lakehouses, for structured and unstructured data.Design and develop analytical tools, algorithms, and programs to support data engineering activities, including writing scripts and automating tasks.Ensure optimum performance and identify opportunities for improvement.Perform data ingestion for all types of data, data wrangling, and transformations, and land data in BigQuery.Work with stored procedures, triggers, data modeling, QlikView, Cloud Functions, Data Fusion, Astronomer, and Airflow. Skills RequiredData/Analytics, Data Warehousing, Data Modeling Skills PreferredGoogle Cloud Platform (Google Cloud Platform) Experience Required4+ years of data engineering work experienceExperience with Google Cloud Platform (Google Cloud Platform) services, including cloud-native application development and deployment.Strong understanding of AI-assisted development tools, such as Gemini Code Assist, OpenCode, and GitHub Copilot, to improve developer productivity.Knowledge of Agentic AI concepts, including AI agents, autonomous workflows, multi-agent systems, and the use of large language models (LLMs) to automate software development and business processes.Experience integrating AI tools into the software development lifecycle, including code generation, debugging, testing, and documentation.Familiarity with cloud AI services on Google Cloud Platform, such as Vertex AI, Gemini models, and AI APIs, is a plus. Experience PreferredExperience with Google Cloud Platform (Google Cloud Platform) services, including cloud-native application development and deployment.Strong understanding of AI-assisted development tools, such as Gemini Code Assist, OpenCode, and GitHub Copilot, to improve developer productivity. Education RequiredBachelor's Degree Education PreferredMaster's Degree ## Description We are responsible for designing, building, and maintaining data solutions, including data infrastructure and pipelines, for collecting, storing, processing, and analyzing large volumes of data efficiently and accurately. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The Cloud is Calling: Answer with In-Demand Skills](https://www.wearedevelopers.com/videos/945-the-cloud-is-calling-answer-with-in-demand-skills) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) ## Related Articles - [Got AI ideas but no money? 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