Senior Analytics Engineer

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

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

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