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Catalog Integration Engineer

Catalog Integration Engineer

This job has closed but is shown for context on data science work at Trove.

About Trove Recommerce

Recognized in 2020 by FastCo as one of the world's most innovative companies, Trove powers resale for the world's most inspired brands and retailers.  We provide brands with the technology and logistics to own the secondary market for their products.  With our white-label capabilities, our partners reap the rewards of managing their own resale market by accelerating long-term revenue, increasing customer loyalty, gaining new customers and boosting store and site traffic.  Resale is a revenue and customer engagement opportunity growing at 5 times the rate of e-commerce and 21 times the rate of traditional retail.  We power in store and online retail for leaders such as Patagonia, REI, Eileen Fisher, Arc’teryx, and Taylor Stitch.


About the Catalog Integration Engineer

This role will build the tools and processes necessary to ensure quality and reliability of the data Trove’s innovative single-sku processing technology depends on. Our core products leverage and augment our partners’ existing product catalogs to power Trove’s internal operations as well as our partners’ resale and trade-in storefronts. As the Catalog Integration Engineer, you will drive improvements in the catalog ingestion processes, identify catalog-driven improvements to the ecommerce customer experience, and enable operational efficiencies within Trove. This role sits at the intersection of engineering and analysis, and will provide opportunities to build both tools and processes, and continually analyze catalog data to improve outcomes. 

In this position, you will report to the VP of Data, as part of a 7-person team that includes analytics, data science, and data engineering. The Data team exists to convert data into business value, for Trove and our partners. Our team is empowered to solve problems and make business recommendations independently, but also collaborates to design creative solutions to tough problems, offer and receive constructive feedback, and pair on thorny technical challenges. In this role, you will also build strong cross-functional working relationships with leaders of Trove’s Product, Engineering, and Partnerships teams, and will also work closely with data teams within our partner brands and retailers. 

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. 

 Responsibilities include…

  • Define cross-functional, cross-company catalog ingestion process, including initial upload, identifying data issues, resolving with partner’s data team, and coordinating internal processes that depend on the initial catalog ingestion.
  • Consult with both technical and non-technical stakeholders within our partner brands and retailers to communicate findings from initial assessment, optimize data architecture, define mappings between fields, and resolve issues.
  • Identify key attributes of catalog data that will improve the customer experience or enable operational efficiency. Define derived fields that map raw catalog data to these attributes.

Projects might include…

  • Design process to upload draft catalog into a sandbox environment
  • Create tools to visualize and assess catalog data quality from both sandbox and production - missing values, outliers, inconsistencies. Create process to flag and resolve data anomalies for new and existing partners.
  • Create documentation for new and prospective partners to ensure they understand standards, best practices, and how catalog data quality impacts the resale program.
  • Analyze catalog to identify how we can map existing data to new fields in order to improve customers’ ability to filter products based on more intuitive, user-friendly fields. 
  • Partner with other Trove data team members to optimize catalog data to improve our resale and trade in pricing algorithms. 

 As for necessities, you have...

  • You enjoy both deeply technical challenges and collaborating cross-functionally to translate data insights into action within the business. You may consider yourself an analytics engineer, an engineer who loves to think about business impact, or an analyst who loves building for scale.
  • You understand the importance of high quality data and rigorous process in building great products. The phrases “strong data governance” and “engineering best practices” bring a smile to your face. 
  • You enjoy project management, and have demonstrated an ability to solve thorny problems and effectively manage work streams from multiple contributors on a cross-functional project.
  • You enjoy working collaboratively with many different teams, and can clearly communicate technical requirements to both technical and non-technical audiences. You enjoy work that is occasionally client-facing. 
  • Manual work makes you cringe, and you automate routine tasks regularly.
  • You aren’t afraid of VLOOKUPS or deeply nested IFs in Excel or Sheets, but you’d rather write SQL. 

 Bonus points if you...

  • Ecommerce experience
  • Experience with our stack: s3, Redshift, dbt, Looker 

 

Trove is proud to be an equal opportunity company and is an affirmative action employer. We believe that diversity and gender balance will help us reach our potential. We are committed to equal opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or veteran status. We will consider qualified applicants with arrest and conviction records for employment.

 

 

 

 

 

This job has closed but is shown for context on data science work at Trove.
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