Business Analytics Architect

Muck Rack

Contract type

Ongoing

Work mode

100% remote

Experience

Senior · 7+ years

Job description

Define and drive the target architecture for an AI-first enterprise data and analytics platform, establishing technical direction and patterns to modernize and consolidate the analytics technology stack
Architect scalable data infrastructure, ingestion and transformation frameworks, storage models, and integration patterns across Snowflake, Databricks, dbt, Python, SQL, and related systems
Design governed semantic data layers and supporting architecture for AI agents, natural language querying, conversational analytics, and other AI-powered data experiences
Establish architecture patterns for retrieval, APIs, and integrations that allow AI agents and applications to securely discover, understand, and interact with trusted enterprise data
Lead the evolution of data governance, security, privacy, access control, and compliance patterns across the analytics stack
Establish and champion engineering standards for data modeling, testing, observability, CI/CD, documentation, deployment, and system integration
Provide technical leadership and mentorship to Analytics Engineers
Company mission
Information not specified

Core technologies

Python (Programming Language)SQL

7+ years of experience designing and evolving modern data and analytics architectures, including architectural decisions spanning multiple systems, teams, or business use cases
Deep experience with modern cloud data platforms and analytics engineering practices, including Snowflake, Databricks, dbt, Python, and SQL
Experience designing scalable data models, transformation pipelines, semantic or metrics layers, and integration patterns enabling trusted self-service analytics
Experience architecting or implementing AI-enabled data systems such as natural language analytics, AI agents, Retrieval-Augmented Generation (RAG), vector search, or related LLM-powered data workflows
Strong knowledge of enterprise data governance, security, privacy, access control, and data quality practices
Experience establishing engineering practices such as automated testing, CI/CD, observability, version control, and reliable deployment patterns for data and analytics systems
Demonstrated ability to set technical direction, evaluate complex architectural trade-offs, and influence decisions across teams without direct authority
Strong communication skills with the ability to translate complex data and AI architecture into clear decisions, standards, and technical direction
Snowflake, Databricks, dbt, Python, SQL, LLMs, AI Agents
Python (Programming Language)
SQL