Lead Analytics Engineer
Sundays for Dogs
full-time
Posted on:
Location Type: Remote
Location: Ohio • United States
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Job Level
About the role
- 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.
Benefits
- Flexible work arrangements
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
dbtSQLdata modelingautomated testingdata transformationdimensional data modelssemantic data modelsanalytics engineeringdata engineeringcloud data warehouses
Soft Skills
communicationmentoringcollaborationstakeholder engagementproblem-solvingpresentation skillsguidanceorganizational skillstranslating business needsbest practices