Data Architect
Role- Senior Data Architect Remote W2 Contract Senior Data Architect – Contract We are seeking an experienced Senior Data Architect with 10+ years of experience to design and deliver modern, enterprise-scale data platforms supporting analytics, AI/ML, and Generative AI applications. The ideal candidate will have strong hands-on expertise in data architecture, ETL/ELT, Python, SQL, enterprise data warehousing, real-time data processing, and cloud data platforms , along with practical experience building data foundations for modern AI and GenAI solutions. Key Responsibilities & Requirements 10+ years of experience in data architecture, data engineering, or related roles, with a strong background designing enterprise-scale data platforms. Strong hands-on experience with ETL/ELT, Python, SQL, and Enterprise Data Warehousing . Proven experience designing batch and real-time data architectures for large-scale enterprise environments. Strong AI/Generative AI data engineering experience, including RAG (Retrieval-Augmented Generation), vector databases, semantic search, LangChain/LangGraph, AI Agents, Azure OpenAI, AWS Bedrock , or similar technologies. Strong understanding of how enterprise data platforms support modern AI/ML and Generative AI applications , including data preparation, retrieval, context management, and AI-ready data pipelines. Treasure Data / Treasure Data CDP experience is a key requirement. Candidates with hands-on, production-level experience implementing or supporting Treasure Data solutions will be strongly preferred. Strong experience with real-time analytics, event-driven architectures, and streaming data pipelines . Hands-on experience with Apache Kafka is highly preferred. Experience with modern cloud data platforms such as Snowflake, Databricks , or equivalent technologies. Strong experience with cloud data engineering services across AWS, Azure, or GCP . Required experience with Change Data Capture (CDC), Debezium, and incremental data processing . Experience designing and implementing scalable batch + streaming data pipelines . Experience building AI-ready data pipelines, semantic search platforms, vector-based retrieval, and/or RAG infrastructure is a strong plus. Ability to translate complex business and AI/ML requirements into scalable, secure, and maintainable enterprise data architectures . Strong understanding of data quality, governance, scalability, performance, and reliability in enterprise data environments. Core Technology Areas Data Engineering: ETL/ELT, Python, SQL, Enterprise Data Warehousing, CDC, Debezium, incremental processing AI/GenAI: RAG, Vector Databases, Semantic Search, LangChain, LangGraph, AI Agents, Azure OpenAI, AWS Bedrock Streaming & Real-Time: Apache Kafka, event-driven architecture, streaming pipelines, real-time analytics Cloud Data Platforms: Snowflake, Databricks, AWS, Azure, GCP Customer Data Platforms: Treasure Data / Treasure Data CDP Ideal Candidate The ideal candidate is a hands-on data architect who can bridge traditional enterprise data engineering with modern AI/GenAI requirements. They should be comfortable designing architectures that combine enterprise data warehouses, cloud platforms, streaming pipelines, customer data platforms, and AI-ready data infrastructure .