Data Engineer

The Data team at Loop is on a mission to empower merchants with transformative data products that drive success beyond returns. By building tools that merchants love and fostering a robust data culture, the team enables smarter decision-making across the board. As a Data Engineer at Loop, you will significantly impact our ability to solve merchant problems and fulfill merchant needs. You will own all aspects of data availability, quality, and ease of use of our data platforms. ### Responsibilities: - Maintain and optimize existing data pipelines and warehouse solutions for performance, reliability, and cost efficiency. - Support internal analytics and ML teams with data modeling, schema updates, and ad hoc data needs. - Contribute to dbt projects and assist in ensuring data quality, observability, and accessibility. - Write clean, tested, and documented code, and participate in code reviews. - Collaborate with senior data engineers to understand and contribute to new ingestion sources, ML pipelines, and other forward-looking initiatives. - Ensure internal stakeholders can access and use data effectively, enabling faster business insights and decision-making. ### Required Experience: - 4 years of hands-on experience building and maintaining data pipelines and data sets in a cloud environment (Snowflake, GBQ, Redshift, etc.). - 2+ years of Python experience, creating reliable workflows and data processing scripts. - Strong SQL skills and experience with data modeling. - Experience with dbt or similar transformation tools. - Familiarity with distributed systems and ETL/ELT processes. ### Nice to Have: - Experience with data observability, lineage, or governance tools. - Exposure to BI tools and supporting analytics teams. - Experience working on cross-functional data projects. - Familiarity with Fivetran, Kafka, or modern data integration platforms.