Design, build, and maintain reliable, tested, and well documented ETL and ELT pipelines and DBT models
Work with stakeholders across the business to understand data needs and translate them into high quality, reusable data products
Identify gaps and improvement areas across the data ecosystem and shape the analytics engineering roadmap
Build and maintain self-service tools and datasets that allow engineers, data scientists, and analysts to get to insights quickly
Partner with Product Engineering, Data Science, and Analytics teams to enable effective use of the data platform
Investigate and resolve data related bugs and technical issues in platform tooling and DBT models
Contribute to and lead cross-team data projects with a focus on reliability, efficiency, and testability

4 or more years of experience in data engineering, analytics engineering, BI engineering, software engineering, or data science
Strong Python skills with a focus on writing clean, high quality, maintainable code
Advanced SQL skills including writing, tuning, and debugging queries against large, multi-source datasets
Proven experience building ETL or ELT pipelines that are reliable, monitored, and easy to maintain
Experience gathering requirements from stakeholders and translating them into well structured datasets
Comfortable communicating and collaborating across both technical and non-technical teams
Familiarity with the majority of the tech stack listed above

Analytics Engineer

Key skills