Analytics Engineer, Catalog Integration

Recognized by FastCo in 2022 as one of the World Changing Ideas Awards and in 2020 as one of the World's Most Innovative Companies, 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.

About the Analytics Engineer

In this role, you 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 an Analytics Engineer focused on Catalog Integration, you will drive improvements in the catalog ingestion processes, identify catalog-driven improvements to the ecommerce customer experience, enable operational efficiencies within Trove, and help improve our broader data platform’s reliability, resiliency, and scalability. 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.

This position will be a part of the Catalog Integration function, sitting on a broader Data Engineering team, including Machine Learning Engineers and other Analytics Engineers. The Catalog Integration function 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 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. Our primary data tooling includes Jupyter Notebooks, Python, Redshift, and dbt as well as AWS infrastructure like Eventbridge and Lambda.

Responsibilities

Establish subject-matter expertise on Trove’s catalogs and the way they power applications ranging from re-commerce storefronts, trade-in experiences, and item identification.
Consult with technical and non-technical counterparts within Trove’s partners (like Patagonia, Arc’teryx, and Brooks Running) to communicate catalog requirements and trade-offs, develop an understanding of our partners’ catalog data management, and structure and transform partner catalog data appropriately for re-commerce systems during the catalog onboarding process.
Build, manage, and scale data pipelines used to transform, map, validate, and load partner catalog data feeds
Collaborate with a range of internal stakeholders to identify catalog-driven opportunities and dependencies to inform product discovery
Evolve tools, best practices and processes to enable the Catalog Integration team to ensure catalog quality and freshness
Collaborate with Analytics Engineers to assemble complex data sets to address a diverse set of business and data analytics requests

Example Projects

Implement automated checks to monitor catalog data quality
Create tooling to empower product support to address ad-hoc catalog issues or requests
Partner with Machine Learning to identify opportunities to augment partner catalog data

Qualifications

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 enjoy owning problems end-to-end. You 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.
You are energized by the thought of working across a wide array of technologies, project types, and stakeholders.
You have a product-focused mindset. You enjoy digging deep into business requirements and architecting systems that will scale and extend to accommodate those needs.
You have strong communication skills, including communicating complex technical information to a non-technical audience.
You have are able to write modular, maintainable code (in dbt, python or another scripting language).
You have a strong understanding of SQL.

Bonus points if you have...

Experience with our stack: Redshift, dbt, Jupyter Notebooks (with Python), AWS S3, AWS Lambda, AWS Eventbridge
Experience with infrastructure-as-code tools like Terraform
Experience with e-commerce data systems like PIMs (i.e. Salsify) and e-commerce platforms (like Shopify or Salesforce Commerce Cloud)

The annual compensation range for this position is $94,660-$137,413 plus competitive bonus and equity.

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