Google Cloud Data Engineer

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.