Analytics Engineer

5+ years of experience in analytics, data science, or equivalent analytical functions. Advanced proficiency in SQL, including window functions, CTEs, and User-Defined Functions. Hands-on experience with dbt or an equivalent tool. Experience with data warehousing platforms and tools like Databricks, Snowflake, BigQuery, or Redshift. A good understanding of Git and version control. A collaborative mindset. Strong analytical skills with comfort in exploratory and descriptive data analysis. Experience integrating dbt into cloud-based data pipelines (preferred). Experience with data orchestration tools like Airflow or Dagster (preferred). Familiarity with reverse ETL using tools like Census or HighTouch (preferred). Understanding of data warehousing concepts and modern data architectures (preferred). Experience with data documentation (preferred). Familiarity with using AI tools to accelerate development (preferred).

Write and maintain dbt models. Debug SQL logic. Translate business requirements into dependable datasets. Build logical data models and automated data quality checks. Partner with data engineers, analysts, and stakeholders. Use dbt and software engineering best practices to build, maintain, and document business data models. Develop scalable, efficient data marts. Craft clean, modular, and well-documented SQL code. Troubleshoot and refactor existing data models. Optimize queries for performance and cost-effectiveness. Collaborate with data engineers to optimize data pipelines. Create and maintain thorough documentation of data models and analytical processes. Advocate for best practices in data modeling, data governance, analysis methodologies, and model testing.