Senior Analytics Engineer

Ddn; New York (NY); On-site; USD 120,000 - 160,000; Full time

Job summary

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

Collaborate with data engineers and analysts to build scalable, well-documented models, dashboards, and semantic layers. Strong SQL, dbt, Python, and cloud warehouse experience are essential.

Qualifications

• 5+ years in analytics engineering, data engineering, or a similar data-focused role.
• Expert-level SQL including 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 Sigma or Looker.
• Strong Python skills for data analysis, automation, or pipeline work.
• Solid understanding of data quality practices including testing, monitoring, documentation.
• Strong communication skills and ability to translate technical concepts for business stakeholders.
• Bachelor’s degree in a quantitative field or equivalent practical experience.

Responsibilities

• Data modeling — design, build, and maintain dbt models for analytics datasets.
• Data quality — implement testing, monitoring, and documentation for trusted data.
• BI & semantic layer — build Sigma data models and dashboards for self-serve analytics.
• Collaboration — translate analytical needs into scalable data models with stakeholders.

Skills

SQL

Data quality practices

Data storytelling / communication

Dimensional modeling

BI collaboration

Education

Bachelor’s degree in quantitative field

Tools

dbt

BigQuery

Snowflake

Redshift

Sigma/Looker

Python

Job description

The Role

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