Senior Data Architect

TMS

. Design and implement production-grade enterprise data architectures .

Posted 9/22/2026contractRemote • Oregon • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in designing and implementing production-grade enterprise data architectures, with a strong focus on ETL/ELT processes, AI/Generative AI data engineering, and real-time analytics. Proficient in integrating cloud data platforms and building AI-ready data pipelines to support modern data applications.

Highest-signal resume keywords

Data Engineering ExperienceETL/ELT ProficiencyAI/Generative AI Data EngineeringEnterprise Data Warehousing/Lakehouse ArchitectureReal-Time Analytics and Streaming Data Pipelines

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLETLELTData ArchitectureData WarehousingReal-Time Data ProcessingIncremental Data ProcessingCDCDebezium

Tools & Technologies

Treasure DataAWSAzureGCPSnowflakeDatabricksApache KafkaAzure OpenAIAWS BedrockVertex AI

Industry Keywords

Data PipelineEvent-Driven ArchitectureStreaming DataAI-Ready Data PipelinesSemantic SearchRAG InfrastructureVector DatabasesLangChainLangGraphAI Agents

Tech Stack

Tools & technologies

ApacheAWSAzureCloudETLGoogle Cloud PlatformKafkaPythonSQL

About the role

Key responsibilities & impact

Design and implement production-grade enterprise data architectures
Build and support hands-on ETL/ELT, Python, and SQL data pipelines
Design enterprise data warehouse/lakehouse platforms supporting modern AI/ML and Generative AI applications
Design batch and real-time data architectures
Build real-time analytics, event-driven architectures, and streaming data pipelines
Implement CDC/incremental data processing using CDC or Debezium
Develop AI-ready data pipelines, semantic search, RAG/vector-search infrastructure, and Generative AI data architectures
Integrate enterprise data with platforms such as Azure OpenAI, AWS Bedrock, Vertex AI, Databricks Mosaic AI, or Snowflake Cortex
Work with Treasure Data / Treasure Data CDP and cloud data platforms including AWS, Azure, GCP, Snowflake, or Databricks

Requirements

What you’ll need

10+ years of Data Engineering/Data Architecture experience; the posting also states 15+ years of experience
Strong hands-on ETL/ELT, Python, and SQL experience
Enterprise Data Warehousing/Lakehouse architecture experience
Strong AI/Generative AI data engineering experience, including RAG, vector databases, LangChain/LangGraph, AI Agents, Azure OpenAI, AWS Bedrock, or similar technologies
Production experience with Treasure Data / Treasure Data CDP
Real-time analytics, event-driven architecture, and streaming data pipelines experience
Apache Kafka experience 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
Experience designing batch and real-time enterprise data architectures
Experience building AI-ready data pipelines, semantic search, or RAG infrastructure is a plus
Experience personally designing and implementing production-grade data architecture, rather than only maintaining existing ETL jobs

Benefits

Comp & perks

Remote work option
Contract role
Confidential handling of applicant information according to EEO guidelines