Senior Data Engineering Developer

Quantrics; Manila, Hinoba-an; On-site; PHP 1,500,000 - 2,200,000; Full time

Job summary

Quantrics is seeking a skilled data engineering professional to build and optimize real-time streaming pipelines for secure enterprise data routing. You will integrate generative AI with enterprise knowledge bases, ensuring accurate conversational agent performance and low-latency storage for session data.

You will design scalable architectures, guide engineering tasks, and implement testing to ensure system stability.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related quantitative field.
• Active Google Professional Data Engineer certification.
• 3+ years in GCP data ecosystem tech (BigQuery, BigTable, Firestore).
• 3+ years of real-time streaming pipelines (Pub/Sub, Cloud Functions, Dataflow).
• 1+ year in LLM orchestration and generative AI integration with enterprise data grounding.
• 2+ years with conversational AI platforms (Google CCAIP, Dialogflow CX).
• 2+ years in Terraform and IAM-based security governance.

Responsibilities

• Build and optimize real-time streaming pipelines for voice and chat data routing.
• Integrate generative AI solutions with enterprise knowledge bases for accurate conversational agent performance.
• Maintain low-latency databases for secure storage of session states and metadata.
• Design architectures and blueprints for scalable, resilient systems.
• Delegate and manage engineering tasks to boost productivity and capability development.
• Develop and run tests to identify issues and ensure system stability.
• Collaborate with stakeholders to align requirements and ensure project success.
• Oversee automated PII redaction workflows to ensure data privacy before storage.

Skills

GCP Data Ecosystem

Real-time Streaming

Generative AI Integration

Conversational AI

Infrastructure as Code & Security

Education

Bachelors in CS/Engineering

Google Professional Data Engineer

Tools

Terraform

Pub/Sub

Dataflow

BigQuery

BigTable

Firestore

Job description

• Build and optimize real-time streaming pipelines to ensure efficient routing of voice and chat session data into enterprise data platforms
• Integrate generative AI solutions with enterprise knowledge bases to ensure accurate and context-aware conversational agent performance
• Maintain and configure low-latency databases to ensure secure and reliable storage of session states and operational metadata
• Design system architectures and technical blueprints to ensure scalable, resilient, and high-performance solutions
• Delegate and manage engineering tasks to ensure effective team productivity and capability development
• Develop and execute testing processes to identify system issues and ensure quality and stability in deployed solutions
• Collaborate with stakeholders to align requirements, manage expectations, and ensure successful project delivery
• Oversee automated PII redaction workflows across voice and text streams to ensure full compliance with data privacy requirements prior to storage.

COMPETENCIES

Core Competencies (Must-have Competencies)

• GCP Data Ecosystem Expertise - Ability to design and manage data solutions using BigQuery, BigTable, and Firestore to support scalable analytics and storage
• Real-time Streaming Pipeline Development - Ability to build and manage high-throughput streaming systems to support continuous data ingestion and processing
• Gemini Enterprise Agent Integration - Ability to implement and optimize generative AI solutions grounded in enterprise data to support conversational accuracy
• CCAIP and Conversational AI Implementation - Ability to deploy and manage voice and chat AI systems to enhance customer interaction experiences
• Infrastructure as Code and Security Governance - Ability to automate infrastructure deployment and manage access controls to ensure secure cloud environments

Complementary Competencies (Good-to-have Competencies)

• Data Redaction and Privacy Engineering - Ability to implement PII masking solutions to support regulatory compliance and data protection
• API and Integration Management - Ability to design and manage APIs and communication protocols to support system interoperability
• Stakeholder Collaboration - Ability to effectively communicate and align with technical and non-technical stakeholders to support project success
• Prioritization and Autonomy - Ability to manage multiple tasks independently while focusing on critical objectives
• Hands-On Software Development - Ability to write high-quality code while contributing to architectural and leadership responsibilities

QUALIFICATIONS

Educational Qualification/s

• Bachelor’s degree in Computer Science, Engineering, or a related quantitative field

Professional Qualification/s

• Active, verified Google Professional Data Engineer certification
• Minimum of 3+ years of experience in GCP data ecosystem technologies including BigQuery, BigTable, and Firestore
• Minimum of 3+ years of experience in real-time streaming pipelines using Pub/Sub, Cloud Functions, and Dataflow
• At least 1+ year of experience in LLM orchestration and generative AI integration using enterprise data grounding techniques
• Minimum of 2+ years of experience with conversational AI platforms such as Google CCAIP and Dialogflow CX
• Minimum of 2+ years of experience in infrastructure as code using Terraform and cloud security governance using IAM roles
• Strong experience in designing system architecture, debugging complex pipelines, and ensuring system performance
• Proficiency in programming languages such as Python, Java, or Go
• Strong analytical, problem-solving, and stakeholder communication skills

Work Conditions

• Work Schedule: Monday to Friday, Golden Hours (aligned to 4 AM ET to 1 PM ET)
• Shift: 9-hour workday (including 1-hour break)
• Locations: GCC Philippines, Bell India, and Bell Morocco
• Overtime/On-call: May be required based on project needs