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# Analytics Engineer

- **Company:** Ramsey Solutions
- **Location:** Nashville, TN, United States
- **Experience:** Experienced
- **Salary:** $88,920.0 - $120,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Business Logic, Cloud Database, Data Governance, Extract Transform Load (ETL), Data Mart, Data Warehousing, Python (Programming Language), Software Tools, SQL Databases, Data Pipelines, Amazon Redshift
- **Published:** July 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=19ba00343c21e2d8

## About the Role

* You have 4+ years of experience building data pipelines and data warehouses, with hands-on skill in Python, SQL, and ETL/ELT development.
 * You've worked with tools like dbt and cloud data warehouses such as AWS Redshift, and you pick up new tools fast when you haven't.
 * You'd rather be heads down building a data product that solves a real business problem than sitting in meetings talking about it.
 * You're self-sufficient and intellectually curious, the kind of person who digs into a hard, ambiguous problem instead of waiting to be told what to do.
 * You enjoy teaching and mentoring others, and you're just as comfortable explaining a data model to a teammate as you are building it.
 * You care about driving results, and you know how to turn that drive into shipped work your team can count on.

## Description

* Building, maintaining, and optimizing data warehouses and data marts that provide reliable, high-quality data for analytics and reporting.
 * Designing, developing, and supporting scalable data pipelines and ETL/ELT processes using modern data engineering tools and technologies.
 * Developing and maintaining trusted dashboards, reports, and key business metrics that serve as the single source of truth for stakeholders.
 * Monitoring and improving data quality by implementing validation, testing, and monitoring processes to ensure accuracy, consistency, and reliability.
 * Collaborating with technical and non-technical teams to deliver data products that support informed decision-making.
 * Building and maintaining expertise in core business data and analytical models to provide accurate insights and recommendations.
 * Documenting data models, business logic, and processes to promote transparency, consistency, and long-term usability.
 * Recommending and implementing best practices for data modeling, analytics engineering, and data governance across the organization.


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