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# Senior Analytics Engineer

- **Company:** DDN, LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $150,000.0 - $185,000.0
- **Contract:** Permanent contract
- **Skills:** Sql Data Warehouse, Data Analysis, BigQuery, Software Documentation, Continuous Integration, Information Engineering, Data Governance, Data Warehousing, Dimensional Modeling, Python (Programming Language), Performance Tuning, Raw Data, Salesforce.Com, SQL Databases, Enterprise Data Management, Great Expectations (Foster Youth College-readiness and Support Program), Snowflake, Data Layers, Looker Analytics, Data Pipelines, Workday, Amazon Redshift
- **Published:** October 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=b7fdaa72f11a2e9e

## About the Role

* 5+ years in analytics engineering, data engineering, or a similar data-focused role
 * Expert-level SQL including experience with complex joins, window functions, CTEs, and performance tuning
 * Strong experience with dbt for building and maintaining transformation pipelines
 * Hands-on experience with a cloud data warehouse (BigQuery, Snowflake, Redshift, or similar)
 * Understanding of dimensional modeling and data warehouse design patterns
 * Experience building and maintaining BI content (dashboards, data models, semantic layers) in tools like Sigma, Looker, or similar
 * Strong Python skills for data analysis, automation, or pipeline work
 * Solid understanding of data quality practices including testing, monitoring, documentation
 * Strong communication skills and demonstrated ability to translate technical concepts for business stakeholders
 * Bachelor's degree in a quantitative field or equivalent practical experience

Nice to Have

 * Experience with Sigma Computing specifically
 * Familiarity with data quality frameworks (e.g., Elementary, Great Expectations)
 * Familiarity with data governance practices - PII handling, access controls, documentation standards
 * Experience with version-controlled, CI/CD-driven analytics workflows
 * Prior experience in a small data team where you wore multiple hats

## Description

* Data modeling - design, build, and maintain dbt models that transform raw data into clean, reliable datasets for analytics and reporting
 * Data quality - implement and maintain testing, monitoring, and documentation so stakeholders can trust what they're looking at
 * BI & semantic layer - build and maintain Sigma data models and workbooks that give business users self-serve access to data
 * Collaboration - partner with business stakeholders to understand their analytical needs and translate them into scalable, maintainable data models; work with data engineers on source data requirements