Senior Data Engineer

 

 

About Trove Recommerce

Trove powers resale for the world's most beloved brands, extending the life of millions of products and creating more inclusive, less wasteful business models. Trove is the market leader in branded resale and trade-in for world-class brands and retailers such as Canada Goose, lululemon, Patagonia, REI, Levi’s, Arc’teryx, Allbirds, and more. Through its proprietary Recommerce Operating System, Trove is accelerating the shift toward more sustainable business models, foundational for circularity. Over the last decade, Trove has equipped leading brands with technology and operations to create and scale branded resale programs by enabling customer trade-in of items, single-SKU identification and condition grading, site build and maintenance, and customer data collection, analytics and reporting. A Certified B Corporation, Trove is pioneering a new era of retail essential to a more sustainable future.

Recognized by FastCo in 2023, 2022 and 2020 as one of the World Changing Ideas Awards and one of the World's Most Innovative Companies, we continue to gather accolades for our innovative resale technology. In 2023, Trove was recognized as winner for Best Use of Emerging Technology by Modern Retail and selected by Inc as 2023 winner for larger businesses that have grown significantly without losing their focus on serving the best products. The Leading 100 selected Trove as 2023 Trailblazer of the Year for breakout technology startups that are driving innovation in fashion and retail. And most recently awarded the Reverse Logistics Operational Excellence Award for 2024 by the Reverse Logistics Association. Join us for the new era of conscious commerce.

About the Sr. Data Engineer role

We are seeking a skilled Sr. Data Engineer to join our data team. As the Sr. Data Engineer, you will be responsible for making architectural decisions to improve critical data processing, analytics pipelines, developing best practices, and building a platform to support the analytics and machine learning products. You will work to improve the data platform’s reliability, resiliency, and scalability in order to support the data analysts, data scientists, and all of the data stakeholders.  

An ideal candidate brings curiosity, a passion for data, and a deep understanding of the technologies behind data pipelines, data warehousing, big data and analytics. Our current data tooling includes Redshift, Snowflake, AWS, Stitch, dbt, Looker, Hex, Terraform.

Trove has a culture that values excellence, integrity, and creative solutions. We are looking for team members who respect each others’ differences, pursue solutions to hard problems, learn from our mistakes, and challenge the status quo. The Trove team and our partners are working to grow a segment of the retail industry that is truly a win-win - our partners can grow their business, gain new customers, and make retail more sustainable by giving their products a second (or third, or fourth) life. 

What You’ll Do

• Extend and optimize the current ELT pipeline to help assemble complex data sets to address a diverse set of business and data analytics requests. Monitor the performance of data pipelines, troubleshoot and resolve data issues.
• Design and develop data marts based on business requirements and data architecture principles. Optimize data mart schema and queries for performance and scalability.
• Perform data validation and quality assurance activities to ensure accuracy and integrity of data
• Create and maintain documentation for data mart designs, ETL processes, and data mappings
• Evolve tools, best practices and processes to enable the Catalog Integration team to ensure catalog quality and freshness
• Stay up-to-date with the latest data engineering technologies and best practices

Experience You Bring

• Bachelor’s degree in Engineering, or a related field (or equivalent practical experience)
• 8+ years of experience in data engineering or a similar role
• Strong expertise in data modeling, developing and implementing data mart and data warehouse solutions
• Proven experience as a data mart developer or similar role in data warehousing projects with strong working knowledge and understanding of the data warehouse design methods, including data vault and dimensional modeling
• Solid understanding of data modeling concepts (star schema, snowflake schema) and data warehouse design principles
• Strong experience and proficiency in SQL, dbt, Redshift administration, including performance tuning, WLM and DMS
• Proven experience in managing and administrating distributed databases
• Experience in building data lakes, AWS and data-related services (e.g., Athena, S3, Glue)
• Experience with Snowflake and Pytho