C3 Industries

Senior Analytics Engineer

C3 Industries Chicago, Illinois, United States

Alternative Medicine · 1,001-5,000 employees

Yesterday
data-analyst Mid (2-5 yrs) Full-time United States
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About the role

The Senior Analytics Engineer will design, build, and maintain enterprise data models in Snowflake to support reporting across various business units. They will also refactor business logic into governed transformation layers and implement automated data quality testing.

What they look for

Snowflake Power BI SQL Data Modeling dbt Python Git CI/CD Dimensional Modeling Data Pipelines ETL DAX Microsoft Fabric Data Quality Business Intelligence

Requirements

Candidates must have a bachelor's degree and at least four years of experience building production data models and pipelines in a cloud data warehouse. Proficiency in advanced SQL, dimensional modeling, and transformation frameworks like dbt is required.

Full description

JOB SUMMARY:

The Senior Analytics Engineer is responsible for designing, building, and maintaining the enterprise data models that power reporting and analytics across C3 Industries and High Profile Cannabis Shops. Leveraging Snowflake and Power BI, the role transforms raw data into documented, tested, reusable models the business can trust, and pulls the business logic currently embedded in individual reports into a governed transformation layer. This is a hands-on senior individual contributor role with significant influence over how C3 models its data as the company adds business units, systems, and locations.

JOB DUTIES:

Core duties and responsibilities include the following. Other duties may be assigned.

  • Design, build, and maintain transformation models in Snowflake that serve reporting across Retail (High Profile Cannabis Shops), Cultivation, Manufacturing, Marketing, and Finance.
  • Refactor business logic out of Power BI datasets into governed, tested, version-controlled models in the warehouse.
  • Build and maintain ingestion pipelines from C3’s source systems, including consolidation of BigQuery marketing and ecommerce data into Snowflake.
  • Define and apply a consistent modeling approach covering naming standards, grain, conformed dimensions, and a shared product and location master.
  • Implement automated data quality testing and monitoring, and own resolution when tests fail.
  • Document models and lineage so analysts can self-serve without relying on tribal knowledge.
  • Partner with analysts and business stakeholders to translate reporting requirements into durable models rather than one-off extracts.
  • Support the semantic layer and BI tooling, and contribute to evaluation of new platform tools such as Microsoft Fabric, dbt, Airbyte, dlt, Omni, and Sigma.
  • Cross-train with the broader team and contribute to shared ownership of critical pipelines and models.
  • Mentor analysts on SQL, modeling practice, and data quality.

SUPERVISORY RESPONSIBILITIES:

None. This role mentors analysts and leads project work without direct reports.

JOB REQUIREMENTS:

  • Bachelor’s degree in computer science, information systems, analytics, engineering, or a related field; equivalent experience considered.
  • Minimum four years building production data models and pipelines in a cloud data warehouse; Snowflake experience strongly preferred, BigQuery a plus.
  • Advanced SQL, including window functions, performance tuning, and incremental processing patterns.
  • Demonstrated data modeling depth across dimensional modeling, slowly changing dimensions, and designing for reuse across multiple reporting consumers.
  • Hands-on experience with dbt or an equivalent transformation framework, and with ingestion tooling such as Airbyte, dlt, or Fivetran.
  • Working experience with Power BI, including semantic models and DAX; exposure to Microsoft Fabric, Looker, Omni, or Sigma a plus.
  • Proficiency with Git-based workflows, code review, and CI/CD for data.
  • Python or a comparable scripting language for pipeline and automation work.
  • Clear written documentation habits and the ability to work directly with non-technical stakeholders.
  • Cannabis, retail, CPG, or multi-site manufacturing experience a plus.

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