Senior Data Engineering Developer

Summary

Design and build real-time streaming pipelines and integrate generative AI with enterprise data platforms using GCP tools like BigQuery and Pub/Sub.

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

GCP Data Ecosystem Expertise – design and manage data solutions using BigQuery, BigTable, and Firestore
Real-time Streaming Pipeline Development – build and manage high-throughput streaming systems
Gemini Enterprise Agent Integration – implement and optimize generative AI solutions grounded in enterprise data
CCAIP and Conversational AI Implementation – deploy and manage voice and chat AI systems
Infrastructure as Code and Security Governance – automate infrastructure deployment and manage access controls

Data Redaction and Privacy Engineering – implement PII masking solutions
API and Integration Management – design and manage APIs and communication protocols
Stakeholder Collaboration – communicate and align with technical and non-technical stakeholders
Prioritization and Autonomy – manage multiple tasks independently while focusing on critical objectives
Hands-On Software Development – write high-quality code while contributing to architecture and leadership

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

Active, verified Google Professional Data Engineer certification
Minimum of 3+ years of experience in the 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