Senior Analytics Engineer: Snowflake Data Layer

World Acceptance Corporation; Greenville (SC); On-site; USD 110,000 - 160,000; Full time

Job summary

World Acceptance Corporation is expanding its Operations Analytics team to build the analytics data layer, including curated models, marts, and a semantic/metrics layer on Snowflake. You will rewrite and migrate SQL Server objects into Snowflake, ensuring accuracy, documentation, and business alignment.

The role blends engineering rigor with analytical instincts, acting as the translator between Analytics and Data Engineering while delivering self-serve, trusted data products to stakeholders and

Qualifications

• 5+ years combined experience across data engineering and analytics.
• Advanced SQL and hands-on data modeling experience.
• Experience with a cloud data warehouse (Snowflake) and a transformation framework (dbt or equivalent).
• SQL Server / T-SQL and Python—migrating objects to Snowflake.
• Experience building or supporting BI/reporting (Power BI).

Responsibilities

• Build the analytics data layer — curated models, marts, and a semantic/metrics layer.
• Turn business questions into data products with performant SQL and documented datasets.
• Write engineering-grade code with version control and peer review.
• Migrate SQL Server models, stored procedures, and jobs to Snowflake.
• Own data reliability: checks for freshness, volume, schema, and business rules.

Skills

Advanced SQL

Data modeling

Snowflake

dbt

Python

Airflow

Power BI

T-SQL

Data warehousing

Data governance

Tools

Snowflake

dbt

Airflow

Git / CI/CD

Job description

World Acceptance Corporation is expanding its Operations Analytics team to build the analytics data layer, including curated models, marts, and a semantic/metrics layer on Snowflake. You will rewrite and migrate SQL Server objects into Snowflake, ensuring accuracy, documentation, and business alignment.

The role blends engineering rigor with analytical instincts, acting as the translator between Analytics and Data Engineering while delivering self-serve, trusted data products to stakeholders and