GCP Data Cloud Architect AI
Listed on 2026-06-18
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IT/Tech
Data Engineering, Data Warehousing
Brief Description
About Us
At Fresh Direct, we are reinventing the grocery experience. Since day one, our mission has been simple: bring the best, freshest food directly from the farm to people’s homes — faster, fresher, and smarter than anyone else. We’re not just a food company. We’re a technology‑powered, customer‑obsessed team building one of the most innovative end‑to‑end food supply chains in the industry.
From proprietary routing systems to our state‑of‑the‑art fulfillment center, every part of our business is designed to deliver unmatched quality, convenience, and care. We partner directly with farmers, fishermen, and artisans to source the highest quality ingredients — then use smart data, automation, and logistics to deliver them at peak freshness. It’s grocery shopping reimagined — and we’re just getting started.
If you’re passionate about innovation, care deeply about what people eat, and want to help build the future of food, we’d love to meet you.
GCP Cloud Data Architect with foundational experience in cloud data platforms and a strong interest in building expertise in Big Query, AlloyDB, Data pipelines, and modern data processing tools. In this role, you will support the development of scalable data solutions on GCP, assist with cloud migration initiatives, and contribute to building pipelines using technologies such as Dataflow, Dataproc, dbt and Cloud Composer.
You will also gain exposure to data transformation frameworks like Dataform and AI/ML use cases. As a Data Architect, you will help enable:
- Advanced Supply Chain Intelligence:
Support development of scalable pipelines using Big Query, AlloyDB, Cloud Storage, Dataflow, Dataproc and Dbt for processing large‑scale batch and streaming data used in inventory and forecasting. - Customer 360 & Personalization:
Assist in integrating transactional and behavioral data using Pub/Sub and Dataflow and help prepare datasets for downstream analytics and personalization. - Real‑time Operational Intelligence:
Contribute to event‑driven pipelines and workflow orchestration using Cloud Composer for operational reporting and KPI tracking. - Strategic Data Products:
Help build and maintain data models and curated datasets that support analytics and reporting across business teams.
This is a hands‑on role designed to help you grow into a senior architect by working on real‑world data challenges in a modern cloud environment.
What You’ll Do- Assist in designing and implementing data warehouse solutions on GCP using Big Query, AlloyDB, Cloud Storage, Dataflow, Dbt and Dataproc
- Support cloud migration activities, including data validation, testing, and pipeline development
- Develop and optimize SQL queries for analytics and reporting
- Build and maintain batch and streaming data pipelines using Dataflow and Pub/Sub
- Support workflow orchestration and scheduling using Cloud Composer (Airflow)
- Contribute to data transformation and modeling using Dataflow, Dataproc, Dataform, Dbt or similar tools
- Assist in building and maintaining data models for analytics and reporting
- Support data governance initiatives such as data quality checks, metadata tagging, and access controls
- Assist with preparing datasets and pipelines for AI/ML use cases using Vertex AI
- Collaborate with engineering, data, and product teams to understand and implement data requirements
- Monitor and troubleshoot data pipelines to ensure reliability and performance
Document data processes, workflows, and architecture components.
What You’ll Bring- 2–5 years of experience in data engineering, data analytics, or cloud‑based data platforms
- Strong SQL skills and experience working with large datasets
- Experience in GCP services such as Big Query, AlloyDB, Dataflow, Dataproc, Cloud Storage, Dataform, Dbt or Pub/Sub
- Exposure to Python or similar programming language
- AI/GenAI for Data Engineering:
Experience leveraging LLM‑based tools such as Claude, ChatGPT, or Gemini to enhance productivity in GCP data engineering workflows—e.g., generating SQL/Big Query queries, writing Dataflow or Dataproc pipelines, optimizing Dbt/Dataform transformations, automating documentation, troubleshooting data quality issues, and…
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