Senior Data Architect | Remote | 15+ Years of experience at TMS in San Diego, CA, United States
- Company: TMS
- Location: San Diego, CA, United States
- Posted: Sep 23, 2026
- Type: Contract
- Experience: 15+ years
Overview
Role: Senior Data Architect Location: CA (Remote) Duration: 12+ Months Experience: 15+ Years Job Description Designing batch + real-time enterprise data architectures. Building AI-ready data pipelines, semantic search, and RAG infrastructure.
Job description
- Role: Senior Data Architect
- Location: CA (Remote)
- Duration: 12+ Months
- Experience: 15+ Years
- Job Description
Responsibilities
- Designing batch + real-time enterprise data architectures.
- Building AI-ready data pipelines, semantic search, and RAG infrastructure.
- Integrating enterprise data with AI platforms like Azure OpenAI, AWS Bedrock, etc.
Requirements
- We are looking for a 10+ years experienced Senior Data Architect for a contract role.
- • Must have strong hands-on ETL/ELT, Python, SQL, and Enterprise Data Warehousing experience.
- • AI/Generative AI data engineering experience is strongly required— RAG, vector databases, LangChain/LangGraph, AI Agents, Azure OpenAI, AWS Bedrock, etc.
- • We are specifically interested in candidates who understand how enterprise data platforms support modern AI/ML and Generative AI applications.
- • Treasure Data / Treasure Data CDP experience is a key requirement — please prioritize candidates with real production experience.
- • Strong experience with real-time analytics, event-driven architecture, and streaming data pipelines.
- • Hands-on Apache Kafka experience is highly preferred.
- • Experience with Snowflake, Databricks, or equivalent cloud data platforms.
- • Strong experience with AWS, Azure, or GCP data engineering services.
- • CDC or Debezium and incremental data processing experience is required.
- • Candidate should have experience designing batch + real-time enterprise data architectures.
- • Experience building AI-ready data pipelines / semantic search / RAG infrastructure will be a major plus.
- • Please do not submit traditional ETL/BI only profiles.
- Specific Ask: Please submit candidates who have Treasure Data + Real-Time Analytics + Enterprise
- ETL/Data Warehouse experience, ideally combined with Kafka and Generative AI.
- Does the candidate have 10+ years of Data Engineering / Data Architecture experience?
- Does the candidate have strong hands-on ETL/ELT, Python, and SQL experience?
- Does the candidate have enterprise Data Warehouse / Lakehouse experience?
- Does the candidate have hands-on Treasure Data / Treasure Data CDP experience?
- How many years of Treasure Data experience does the candidate have?
- Does the candidate have real-time analytics / streaming experience?
- Does the candidate have strong Snowflake or Databricks experience?
- Does the candidate have experience designing cloud data architectures on AWS, Azure, or GCP?
- Does the candidate have Generative AI data engineering experience?
- Does the candidate have experience building RAG or vector-search pipelines?
- Does the candidate have experience with LangChain, LangGraph, LlamaIndex, or AI Agents?
- Does the candidate have experience integrating enterprise data with Azure OpenAI, AWS
- Bedrock, Vertex AI, Databricks Mosaic AI, or Snowflake Cortex?
- Has the candidate personally designed and implemented production-grade data architecture,
- rather than only maintaining existing ETL jobs?
Skills
Required
- ETL/ELT
- Python
- SQL
- Enterprise Data Warehousing
- AI/Generative AI data engineering
- RAG
- Vector databases
- LangChain/LangGraph
- AI Agents
- Azure OpenAI
- AWS Bedrock
- Treasure Data / Treasure Data CDP
Preferred
- Apache Kafka
- Snowflake
- Databricks
- AWS
- Azure
- GCP
- Semantic search
- RAG infrastructure