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

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

Senior Data Engineer

Key skills