GCP Data Engineer (AI Experience)

Vsg Business Solutions
Hartford, CT, United States
8 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

Agile Methodology Artificial Intelligence Airflow BigQuery Cloud Storage Data Infrastructure Data Profiling Distributed Systems Electronic Data Interchange (EDI) Github Python (Programming Language) Linux System Administration
+13 more
MongoDB NoSQL Performance Tuning DataOps Shell Script Freeform SQL Google Cloud Apache Kafka Data Management Google Gemini Stream Processing GPT Data Pipelines

Requirements

Required - Must have experience AI - GPT, Gemini. Must be able to demonstrate how they use it. Using it as business use cases on resume. Must be highlighted clear on the resume Required - minimum 7 years of proven hands-on experience with GCP data services. Preferred - GCP Google Cloud Professional Data Engineer Certification. Required Strong understanding of distributed systems and data engineering best practices. Required Excellent communication and documentation skills. Required Ability to work independently and collaboratively in a fast-paced environment. Required experience in Agile methodology with preferred experience in SAFe methodology Required good communication and collaborative skills Required experience working in onshore/offshore support model collaborating work with offshore teams. Preferred experience working with GitHub, RTC, automation tools. Required - minimum 3 years of proven hands-on experience in the following: Design and implement robust data pipelines using Google Cloud Platform (GCP) services such as BigQuery, Cloud Storage, and Pub/Sub. Develop and manage workflows using Cloud Composer (Apache Airflow) for efficient scheduling and orchestration. Write clean, efficient, and scalable code in Python, leveraging advanced programming techniques. Craft complex SQL queries in BigQuery, including window functions, CTEs, and performance tuning strategies. Build and maintain real-time data processing systems using Apache Kafka. Model and manage NoSQL databases, particularly MongoDB, with a focus on scalable schema design. Utilize Shell scripting and perform Linux system administration tasks to support data infrastructure. Conduct data profiling and implement validation techniques to ensure data quality and integrity. Develop and maintain API integration scripts for seamless service automation and data exchange. Troubleshoot and resolve data-related issues with strong analytical and problem-solving skills. Create and maintain data flow diagrams to clearly communicate architecture and pipeline logic to stakeholders. Develop and manage workflows using Cloud Composer 3

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