We’re looking for a Senior Analytics Engineer to own the transformation and modeling layer of DDN’s enterprise data platform. You’ll turn raw data from Salesforce, Workday, product systems, and other sources into trusted, well-documented datasets that stakeholders across Sales, Finance, Product, and Operations actually use to make decisions. You’ll work closely with data engineers who manage ingestion and infrastructure, and with analysts and business partners who consume what you build.
What You’ll Own
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
Your Experience Includes
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
Skills Required
- 5+ years of experience in analytics engineering, data engineering, or a similar data-focused role
- Expert-level SQL, including complex joins, window functions, common table expressions, and performance tuning
- Strong experience with dbt for building and maintaining transformation pipelines
- Hands-on experience with a cloud data warehouse such as BigQuery, Snowflake, Redshift, or similar
- Understanding of dimensional modeling and data warehouse design patterns
- Experience building and maintaining BI content, including dashboards, data models, or semantic layers, in tools such as Sigma or Looker
- Strong Python skills for data analysis, automation, or pipeline work
- Understanding of data quality practices, including testing, monitoring, and documentation
- Strong communication skills and ability to translate technical concepts for business stakeholders
- Bachelor's degree in a quantitative field or equivalent practical experience
- Experience with Sigma Computing
- Familiarity with data quality frameworks such as Elementary or Great Expectations
- Familiarity with data governance practices, including PII handling, access controls, and documentation standards
- Experience with version-controlled, CI/CD-driven analytics workflows
- Prior experience working on a small data team with multiple responsibilities
What We Do
DDN is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions, the company delivers AI, Data Management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations. DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world’s leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.
