Sundays for Dogs is a founder-led, direct-to-consumer brand focused on reimagining pet food to enhance the quality time dog owners spend with their pets. They are seeking a Lead Analytics Engineer to build their analytics foundation from scratch, creating reliable transformation pipelines and optimizing data models to support business-critical reporting and analysis.
Responsibilities:
- Develop and maintain high-quality dbt models, tests, documentation, and workflows to create reliable transformation pipelines
- Build and optimize dimensional and semantic data models that power business-critical reporting and analysis
- Partner with data consumers and stakeholders to translate business questions into well-defined datasets and semantic definitions
- Design, build, and maintain the semantic layer for visualization tools such as Omni Analytics, Looker, or Sigma
- Ensure data quality and trust by implementing automated testing, monitoring, and observability best practices
- Collaborate with Engineering to scale pipelines, improve performance, and reduce latency in the analytics stack
- Own the data modeling strategy and governance standards, including conventions, documentation, and onboarding practices
- Mentor and guide other analytics engineers and data team members on best practices
Requirements:
- 6+ years of experience in analytics engineering, data engineering, or related roles
- Deep expertise with dbt, including advanced modeling, macros and testing frameworks
- Strong SQL skills and experience with cloud data warehouses (e.g., Snowflake, BigQuery, Databricks)
- Significant hands-on experience developing in modern visualization layer platforms such as Omni Analytics, Looker, or Sigma
- A solid understanding of DTC and ecommerce metrics such as CAC, LTV, cohort analysis, retention and forecasting
- Experience translating business needs into structured, reusable analytics models
- Excellent communication skills and ability to present technical concepts to business stakeholders
- Experience with data observability and monitoring tools
- Familiarity with reverse ETL tools and workflows
- Python experience for orchestration or transformation tasks