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# Analytics Engineer

- **Company:** Cracker Barrel Old Country Store, Inc.
- **Location:** Lebanon, TN, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Cloud Database, Software Documentation, Code Review, Information Systems, Continuous Integration, Information Engineering, Data Integrity, Data Transformation, Data Warehousing, Relational Databases, Dimensional Modeling, Github, Power BI, SQL Databases, Technical Data Management Systems, System Availability, Snowflake, Information Technology, Data Analytics, Software Version Control
- **Published:** October 1, 2026
- **Apply:** https://dejobs.org/x/x/873792188F7C4EEA97796E12DF036EF7/job/

## About the Role

* Bachelor's Degree in Computer Science, Information Systems, Data Analytics, Mathematics, Statistics, Engineering, or a related field, OR an equivalent combination of education, certification, and relevant work experience.
 * 4+ years of experience in analytics engineering, business intelligence, data warehousing, data engineering, or advanced analytics.
 * 3+ years of advanced SQL development experience.
 * Experience developing analytical solutions within a cloud-based data platform.
 * Experience with dimensional data modeling and data warehouse concepts.
 * Experience translating business and reporting requirements into scalable technical data solutions.
 * Experience collaborating across technical and business teams.
 * Advanced SQL development and analytical problem-solving skills.
 * Strong knowledge of relational data structures, data transformation, dimensional modeling, and data warehousing concepts.
 * Working knowledge of dbt development, testing, documentation, dependency management, and deployment practices.
 * Ability to translate business definitions into consistent, reusable, and testable technical logic.
 * Knowledge of data quality controls, source control, peer review, and production support practices.
 * Ability to troubleshoot complex transformation logic and identify root causes across data dependencies.
 * Strong attention to documentation, naming conventions, standards, and repeatable processes.
 * Clear written and verbal communication skills.
 * Ability to work effectively with technical and non-technical stakeholders.
 * Ability to manage assigned solutions through design, development, validation, deployment, and support.
 * Commitment to continuous learning and improvement of analytics engineering practices.

## Description

* Design, develop, test, deploy, and maintain dbt models within Snowflake.
 * Transform curated source data into reusable analytical datasets and business-ready data products.
 * Design dimensional models, including fact tables, dimension tables, conformed dimensions, hierarchies, and documented grain.
 * Develop and support Gold-layer models optimized for enterprise reporting, analytics, and approved AI use cases.
 * Ensure analytical models align with established architecture, naming, SQL, data modeling, security, and documentation standards.
 * Partner with business stakeholders and analysts to translate approved KPI definitions and business rules into governed metric calculations.
 * Build and maintain curated datasets that support Power BI semantic models, certified data sources, and self-service reporting.
 * Support metric and data-product certification by documenting technical logic, source fields, lineage, dependencies, refresh expectations, and known limitations.
 * Implement automated dbt tests and validation controls for uniqueness, completeness, accepted values, referential integrity, freshness, and business rules.
 * Monitor production analytical data products and troubleshoot transformation failures, data anomalies, performance concerns, and unexpected reporting results.
 * Use GitHub and established source-control practices to manage branches, submit pull requests, participate in code reviews, and support controlled deployments.
 * Contribute to CI/CD practices, reusable development patterns, technical templates, and team documentation.
 * Partner with Data Engineering to address upstream dependencies, data availability, scalability, and production support needs.
 * Participate in requirements discovery, solution design, user acceptance testing, and release validation.
 * Provide guidance to analysts and report developers on certified datasets, model usage, metric logic, and data limitations.
 * Assist with training and enablement related to dbt models, governed data products, and certified semantic datasets.
 * Perform other duties as assigned in support of data and analytics initiatives.