Senior Data Engineering Developer II

SPECIFIC DUTIES AND RESPONSIBILITIES

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