GOOGLE CLOUD DATA ENGINEER

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.
• 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.