As a Sr. Data Engineer at Loop, you’ll have a significant impact on our ability to solve merchant problems and fulfill merchant needs. You’ll own the availability, quality, and ease of use of our data platforms. You’ll balance a healthy blend of creativity and structure, and take our data platforms to the next level.
We’ve listed what we think you’ll be spending your time on. We’re growing fast, and growth means the challenges we’ll work on together will change as we lead Loop through new and different phases.
This is an indispensable role with us, so we’ll be looking for you to have examples of when you’ve tackled these challenges throughout your career. We’ve laid out the experience we think is important to set you up for success in this role. But, we appreciate that different humans will solve problems in different ways, so we don’t expect you to fit exactly in a box of requirements.
At Loop, we believe that flexibility and choice are what allow you to do your best work. With our Blended Working Environment, you have options ranging from joining our HQ office (in Columbus, Ohio), opting into a Hub (a location with 4+ team members), or staying totally secluded (our version of remote). Our team is spread across the United States, select provinces in Canada (Ontario & British Columbia), and the United Kingdom. Wherever you live, you can create the work environment that best matches your preferences and lifestyle.
Our tech stack: Fivetran, dbt, Snowflake, Looker, Secoda
What You’ll Do:
- Ensure data availability and quality from OLTP systems to analytics environments.
- Manage and maintain data pipelines and high-volume data storage solutions, optimizing compute and storage consumption.
- Develop and improve the current BI architecture with a focus on data security, quality, timeliness, scalability, and extensibility.
- Analyze source systems, define underlying data sources, and design end-to-end data solutions and architecture.
- Write high-quality code (reliable, readable, efficient, testable), provide quality code reviews, and create comprehensive tests and documentation.
- Develop and implement complex data models, ETL processes, and data warehouse solutions.
- Provide data leadership within the team by informing decisions and offering insights on data usage across the organization.
- Collaborate with machine learning engineers, analysts, and data PMs to ensure data initiatives align with business goals.
- Collaborate with SecOps and Engineering to ensure data security compliance, and the integration of best practices in data management.
Your Experience:
- 5+ years of hands-on experience building and maintaining data pipelines and automating data availability and accuracy.
- Experience with Snowflake or similar cloud platforms.
- Expertise in complex data modeling, ETL design, and handling large databases in a business environment.
- Proven ability in building data lake and data warehouse solutions.
- Advanced skills in writing and optimizing complex SQL.
- Demonstrated efficiency in tracking data lineage, ensuring data quality, and improving discoverability of data.
- Knowledge of Engineering and Operational Excellence best practices.
We're Extra Excited About:
- Knowledge of dbt.
- Experience leading the day-to-day work of a small team.
- Experience building data governance programs.
- Familiarity with Kafka.
Canada
United Kingdom
United States
