Senior Analytics Engineer

DDN; New York (NY); On-site; USD 130,000 - 190,000; Full time

Job summary

DDN is seeking a Senior Analytics Engineer to own the transformation and modeling layer of its enterprise data platform. You will turn raw data from Salesforce, Workday, product systems, and other sources into trusted datasets used by Sales, Finance, Product, and Operations.

You’ll collaborate with data engineers, analysts, and business partners to build scalable data models, ensure data quality, and deliver BI content through Sigma, Looker, and other tools.

Qualifications

• 5+ years in analytics engineering or data-focused role.
• Expert-level SQL with complex joins, window functions, CTEs, and performance tuning.
• Strong dbt experience.
• Hands-on cloud data warehouse experience (BigQuery, Snowflake, Redshift).
• Understanding of dimensional modeling and data warehouse design patterns.
• Experience building BI content (dashboards, data models, semantic layers) in Sigma/Looker or similar.
• Strong Python skills for data analysis and automation.
• Strong communication and ability to translate technical concepts for business.
• Bachelor’s degree in a quantitative field or equivalent practical experience.

Responsibilities

• 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 analytical needs and translate them into scalable, maintainable data models; work with data engineers on source data requirements.

Skills

SQL

dbt

Python

Data modeling

Data quality

Stakeholder communication

Education

Bachelor’s degree in a quantitative field

Tools

Sigma Computing

Looker

BigQuery

Snowflake

Redshift

CI/CD analytics workflows

Job description

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