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Sr Business Intelligence Engineer

Job in Lehi, Utah County, Utah, 84043, USA
Listing for: NetDocuments
Full Time position
Listed on 2026-05-16
Job specializations:
  • Software Development
    Data Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

About the role

We are seeking a highly skilled Senior BI Engineer to take ownership of our Snowflake data platform and help evolve it into a scalable, well‑governed foundation for analytics and AI.

This is a hands‑on engineering role responsible for shaping data architecture, enforcing standards, and building a clean, reliable data layer that supports both business intelligence and AI‑driven use cases. You will report directly to the Director of BI and have significant autonomy in how the platform evolves.

What You’ll Do

Own and Elevate the Data Platform

  • Design and evolve our Snowflake data platform end‑to‑end.
  • Refactor and enhance pipelines, dbt models, and transformations to meet high standards for scalability, performance, and maintainability.
  • Make and drive architectural decisions—not just implement tasks.

Architect for Scale and Clarity

  • Implement and enforce medallion architecture (bronze/silver/gold) with clear separation of concerns.
  • Design and build dimensional models (star schemas) that are intuitive, performant, and durable.
  • Implement SCD Type 2 and other core warehousing patterns correctly and consistently.
  • Establish and enforce standards for schemas, naming, and data contracts.
  • Integrate and normalize data from a wide range of source systems into a coherent, well‑modelled warehouse layer.

Build an AI‑Ready Data Layer

  • Design data models optimized for semantic clarity and AI/LLM consumption.
  • Implement semantic views in Snowflake to enable tools like Claude via MCP.
  • Ensure data is traceable, explainable, and trustworthy.
  • Introduce and enforce data quality testing and validation, schema enforcement and regression safeguards, clear promotion paths from dev → prod, and raise the bar on engineering discipline across the data function.

Leverage AI as a Force Multiplier

  • Use AI tools to accelerate development while maintaining high standards.
  • Guide and validate AI‑generated code—never blindly trust it.
  • Explore agent‑based approaches for anomaly detection and monitoring.

Collaborate and Lead Technically

  • Partner with BI analysts to deliver reliable, well‑modelled datasets (Power BI downstream).
  • Translate ambiguous business requirements into clean, scalable data models.
  • Provide technical direction to a supporting QA/offshore resource (planned).

Documentation & Transparency

  • Build a culture of clear documentation, lineage, and data discoverability.
  • Ensure systems are understandable and maintainable by others.
  • Other duties as assigned.
What You’ll Need to be Successful
  • 5+ years of hands‑on data engineering experience, with a meaningful portion spent owning architecture and driving development—not just executing assigned tasks.
  • Strong experience with Snowflake as a primary warehouse.
  • Advanced SQL skills and experience building production‑grade ELT pipelines.
  • Strong hands‑on experience with dbt for modeling, testing, and transformation, including macros, tests, snapshots, and managing a production dbt project at scale.
  • Experience integrating and normalizing data from many disparate source systems—SaaS APIs, application databases, CRM/ERP, finance systems, event data—into consistent, analytics‑ready models.
  • Deep, hands‑on experience with star schemas and dimensional modeling, SCD Type 2 implementations, layered/medallion architectures.
  • Ability to make trade‑offs and defend decisions (performance vs flexibility, normalization vs usability, etc.).
  • Track record of improving data quality, consistency, and trust.
  • Experience implementing Git‑based workflows and structured SDLC practices for data.
  • Strong instincts around testing, governance, and maintainability.
  • Comfortable setting and enforcing standards across a team.
AI‑First Mindset
  • Demonstrated ability to use AI tools to meaningfully increase output and velocity.
  • Strong judgment to validate and refine AI‑generated work.
  • Interest in applying AI/agents to improve data engineering workflows.
What Will Make You Stand Out
  • Familiarity with Power BI.
  • Familiarity with Salesforce as a data source (objects, schema, Salesforce‑to‑warehouse pipelines).
  • Experience working with or leading offshore/support resources.
What You’ll Love About Net Documents
  • The People!
  • 90 % healthcare premiums company covered.
  • HSA…
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