Hybrid Data Architect for AI-Driven SaaS Platform

Opiniion Inc.; Lehi (UT); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Healthcare plans

401(k) match

Health Savings Account

Parental Leave

Unlimited PTO

Paid Holidays

Wellness Reimbursement

Job summary

Opiniion is a SaaS, AI-first company in Lehi, Utah, seeking a Staff Data Architect to own the data platform end to end. You will shape ingestion, modeling, governance, and analytics-ready pipelines as we scale a hybrid architecture.

You will partner with the Staff Software Architect, balance legacy data with the new platform, and mentor data engineers while guiding platform decisions and data quality practices.

Qualifications

• Extensive experience in data architecture or data engineering.
• Expertise with Databricks or Snowflake.
• Strong modeling and governance experience.
• Experience with ETL/ELT and orchestration tools.

Responsibilities

• Own the architecture of the data platform, including ingestion, transformation, storage, and semantic/BI layers.
• Partner with the Staff Software Architect to co-drive the architecture and rollout of the new platform.
• Balance ownership of the current data platform with architecting the new one during the transition.
• Design and implement data models, governance, and lineage practices across the platform.
• Guide and mentor data engineers through design reviews and hands-on support.
• Evaluate data tools, frameworks, and platform investments, including build vs. buy decisions.

Skills

Data modeling

SQL

Python

Leadership

Communication

Tools

Databricks

Snowflake

Airflow

dbt

Spark

Job description

Opiniion is a SaaS, AI-first company in Lehi, Utah, seeking a Staff Data Architect to own the data platform end to end. You will shape ingestion, modeling, governance, and analytics-ready pipelines as we scale a hybrid architecture.

You will partner with the Staff Software Architect, balance legacy data with the new platform, and mentor data engineers while guiding platform decisions and data quality practices.