Responsibilities
- Close collaboration with data scientists, ML engineers, and product teams to translate requirements into scalable, maintainable data solutions
- Build, document, and maintain robust data pipelines using tools like dbt, Dagster, Snowflake, Estuary, and Airbyte
- Develop deployment and release of functionality through software integration to support devops and CI/CD pipelines
- Design, build, and operate cloud-based (AWS) data infrastructure, optimizing for scale, performance, and cost efficiency as the size of our data grows
- Build frameworks and internal self-service tooling that helps the data team deliver value faster
Requirements
- Bachelor’s degree required, or relevant experience
- 5+ years of prior experience as a software engineer or data engineer in a fast-paced, technical, problem-solving environment
- Proficiency in cloud data warehouse (e.g., Snowflake) best practices, optimization and usage
- Expert in ETL, data modeling and version control, dbt and GitHub preferred
- Develop and implement robust data models that ensure data integrity, consistency, and understandability for both internal and external consumers
- Knowledge and understanding of AWS data ecosystem
- Experience with data extraction tools (Estuary, Airbyte, etc.)
- Experience with programming language like Python, JavaScript
- Experience with Business Intelligence tools, Looker preferred
- Familiarity with data streaming technologies
- Demonstrated experience with continuous integration/continuous deployment tools
- Partner closely with business, engineers, product managers, and other stakeholders to translate business needs into technical solutions
- Ability to work in a fast paced environment and shift gears quickly
- Must be able to work core aligned hours to US Eastern Time / GMT-5
Work Arrangement
Remote (Worldwide)
Additional Information
- Must be able to work core aligned hours to US Eastern Time / GMT-5
