Google Cloud Data Engineer

Veriipro; Charlotte (NC); On-site; USD 100,000 - 145,000; Full time

Job summary

Veriipro is seeking a Google Cloud Data Engineer with 5+ years of experience to design and develop cloud-native data solutions on Google Cloud Platform. You will build scalable pipelines, CI/CD, and IaC while collaborating with cross-functional teams on AI/ML and CCaaS projects.

The role focuses on data quality, security, and performance, leveraging tools like GKE, Pub/Sub, BigQuery, Terraform, and Apigee in an agile environment.

Qualifications

• 5+ years of data engineering and cloud data solutions experience on GCP.
• Experience with CCaaS integrations and contact center migrations.
• Strong communication, stakeholder management and cross-functional collaboration skills.
• Experience working in Agile environments and contributing to product roadmap planning using Jira/Aha.

Responsibilities

• Design and build scalable data pipelines, ETL processes, and data models on GCP.
• Develop secure cloud solutions using GKE, Cloud Run, Cloud Functions, Pub/Sub, BigQuery, Apigee, and Terraform.
• Implement CI/CD pipelines and Infrastructure as Code (IaC).
• Build AI/ML and GenAI solutions using Python, TensorFlow, LLMs, XGBoost, Prophet, and prompt engineering.
• Support the ML lifecycle, including model deployment, monitoring, governance, and optimization.
• Design and support CCaaS solutions, including ACD, skills-based routing, omnichannel, CRM/CTI integrations, SIP/WebRTC, and contact center migrations.
• Develop conversational AI/IVA solutions with NLU/NLP, IVR, STT/TTS, and webhook integrations.
• Ensure data quality, security, reliability, and performance while following Agile and DevOps practices.

Skills

GCP

Data modeling

Spark

Python

CI/CD

TensorFlow

LLMs

GenAI

Prophet

XGBoost

Tools

Terraform

GKE

Cloud Run

Cloud Functions

Pub/Sub

Apigee

BigQuery

Job description

We are looking for a Google Cloud Data Engineer with 5+ years of experience in designing and developing cloud-native data solutions on Google Cloud Platform (GCP). The ideal candidate should have expertise in data engineering, cloud infrastructure, AI/ML, and CCaaS integrations.

Roles and Responsibilities

• Design and build scalable data pipelines, ETL processes, and data models on GCP.
• Develop secure cloud solutions using GKE, Cloud Run, Cloud Functions, Pub/Sub, BigQuery, Apigee, and Terraform.
• Implement CI/CD pipelines and Infrastructure as Code (IaC).
• Build AI/ML and GenAI solutions using Python, TensorFlow, LLMs, XGBoost, Prophet, and prompt engineering.
• Support the ML lifecycle, including model deployment, monitoring, governance, and optimization.
• Design and support CCaaS solutions, including ACD, skills-based routing, omnichannel, CRM/CTI integrations, SIP/WebRTC, and contact center migrations.
• Develop conversational AI/IVA solutions with NLU/NLP, IVR, STT/TTS, and webhook integrations.
• Ensure data quality, security, reliability, and performance while following Agile and DevOps practices.

Required Skills

• Cloud: GCP, GKE, Cloud Run, Cloud Functions, Pub/Sub, Apigee, BigQuery, Google Cloud Storage, Terraform
• Data Engineering: ETL, Data Modeling, Spark, Scala, Hive SQL, BigQuery, Kafka, RDBMS, NoSQL
• Programming & DevOps: Python, Git, Jenkins, Maven, CI/CD
• AI/ML: TensorFlow, LLMs, GenAI, Prompt Engineering, XGBoost, Prophet, SARIMA
• Other: Data Structures, Algorithms, Design Patterns, Observability, Agile

Preferred Qualifications

• 5+ years of software development and cloud data engineering experience.
• Experience with CCaaS implementations and contact center migration projects.
• Strong communication, stakeholder management, and cross-functional collaboration skills.
• Experience working in Agile environments and contributing to product roadmap planning using Jira/Aha.