Architect, Data Platform & AI Analytics

PrinterLogic

Saint George (UT)

On-site

USD 120,000 - 180,000

Full time

8 days ago

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Job summary

Vasion is seeking a Lead Analytics Engineer to serve as the primary technical architect of our data platform. This high-ownership, hands-on role designs and governs analytics from ingestion to semantic layer feeding reporting, while mentoring 1-2 Analytics Engineers.

You will lead AI-powered analytics initiatives and drive the Analytics Engineering roadmap. You will own Snowflake as the data warehouse, ELT pipelines with Airbyte Cloud and Fivetran, and the semantic layer, ensuring reliable data

Qualifications

5+ years in analytics engineering or data engineering.

Responsibilities

Serve as the primary architect of the Snowflake data warehouse (schema design, performance optimization, cost management).
Own ELT pipelines via Airbyte Cloud and Fivetran, ensuring timely data delivery.
Design and maintain the semantic layer and metrics definitions used by AI agents and visualization tools.
Establish and enforce standards for data modeling, pipeline design, testing, and documentation.
Lead the design and development of dbt models, tests, and documentation in production.
Define best practices for project structure, naming conventions, and incremental strategies.
Own dbt DAG health, model performance, and overall project quality.
Own the Analytics Engineering roadmap and align delivery with business needs.
Partner with the BI Manager to triage requests and plan work.
Facilitate sprint planning and backlog grooming to keep the team focused.
Communicate project status, risks, and timelines to both technical and non-technical audiences.
Lead analytics AI strategy and evaluate AI tools/workflows to enhance data delivery and insights.
Prototype LLMs and AI-assisted tooling in the data stack.
Champion AI-curiosity in the BI and Analytics Engineering team.
Stay current on AI/ML capabilities and provide practical recommendations.
Implement and maintain data quality frameworks and alerting.
Document data lineage and ownership in a centralized catalog.
Collaborate with data consumers to build trust in the data.
Mentor 1-2 Analytics Engineers through code reviews and feedback.
Translate business requirements into technical specs for the team.
Help junior members grow SQL, dbt, and data modeling skills.