Senior Data Engineer – GCP (AI & Conversational Analytics)

Locations: Sacramento, CA | Raleigh, NC | Miami, FL (On-site)
Job Type: Full-time

Company Description

Zenith AI is a next-generation AI company helping enterprises harness the power of Artificial Intelligence, Generative AI, and modern data platforms to drive transformation. We specialize in building scalable, production-grade AI systems—from LLM-powered applications to advanced analytics platforms—that enable intelligent decision-making and automation.

Our teams work at the intersection of data engineering, AI engineering, and product innovation, delivering high-impact solutions across industries through deep technical expertise and a strong focus on business outcomes.

Job Description

We are seeking a Senior Data Engineer – GCP to play a key role in building the data foundation for AI-powered conversational analytics platforms. This role focuses on preparing enterprise data for LLM-driven applications, designing semantic layers, and enabling scalable, governed data access for intelligent systems.

You will collaborate closely with AI Engineers, Data Scientists, and Product teams to ensure that data is optimized for natural language querying, insight generation, and advanced analytics use cases.

Key Responsibilities:

• Design, build, and maintain scalable data pipelines on Google Cloud Platform (GCP) for AI and analytics use cases.
• Prepare and transform complex enterprise data for LLM consumption and conversational analytics workflows.
• Develop and manage semantic layers, business logic mappings, and data models that align with business KPIs, taxonomies, and hierarchies.
• Structure data to support natural language querying, automated insight generation, and anomaly detection.
• Partner with AI/ML teams to enable LLM workflows, agent orchestration, and retrieval-augmented architectures (RAG).
• Implement robust data ingestion, transformation, and data quality frameworks for large-scale analytical datasets.
• Support both real-time (live-query) and batch/cached data access patterns based on architectural requirements.
• Ensure data is governed, explainable, and aligned with enterprise definitions for evaluation and user acceptance.
• Collaborate with Data Scientists on validation datasets, ground-truth generation, and model evaluation pipelines.
• Work with architects and stakeholders to ensure alignment with enterprise data governance and scalability standards.
• Contribute to production readiness through testing, monitoring, documentation, and CI/CD best practices.
• Enable scalable design patterns to support expansion into new datasets and advanced AI capabilities.

Qualifications

• 4+ years of experience in Data Engineering, preferably in cloud-based environments.
• Strong proficiency in SQL and Python for data processing and transformation.
• Hands-on experience building scalable data pipelines and ETL/ELT workflows.
• Strong understanding of data modeling, semantic layer design, and analytical data structures.
• Experience with Google Cloud Platform (GCP) services such as BigQuery, Pub/Sub, Cloud Run, and/or Vertex AI.
• Experience with modern data platforms such as Databricks or similar ecosystems.
• Experience working with large-scale enterprise datasets (analytical or transactional).
• Understanding of data governance, role-based access, and enterprise data standards.
• Experience supporting AI/ML or Generative AI use cases, including data preparation for LLMs or retrieval systems.
• Familiarity with data quality validation, monitoring, and testing frameworks.
• Experience with Git-based CI/CD pipelines and modern development workflows.
• Strong communication skills and ability to collaborate across technical and business teams.

Preferred Qualifications

• Experience with conversational analytics, NLP-driven systems, or AI-powered querying platforms.
• Understanding of semantic modeling for LLMs and prompt-aware data design.
• Experience with retrieval-augmented generation (RAG) architectures.
• Exposure to MLOps and AI pipeline orchestration.
• Experience working in regulated enterprise environments with strict governance requirements.
• Proven ability to contribute to knowledge sharing and internal capability building.

Why Join Zenith AI?

• Work on cutting-edge AI and conversational analytics platforms
• Be part of a high-growth, AI-native organization
• Collaborate on LLM-driven, enterprise-scale solutions
• Opportunity to shape next-generation data architectures for AI systems