Job Description
Data Software Engineers are responsible for building and maintaining a “Library of Congress” of the world’s performance product data, along with the supporting systems necessary to maintain on-going completeness and accuracy. In addition to traditional ETL tasks, this work will require collaboration with experts in Natural Language Processing, Statistics and Machine Learning, and Behavioral Economists to develop scalable automation to manage evolving product assortments, their taxonomic relationships, and meta data such as usage and market sentiment. The current target environment includes AWS, Python, and PostgreSQL. Familiarity with collaborative development, git, unit testing, continuous integration, and popular Python libraries is expected. Familiarity with automatic test generation (e.g. QuickCheck style testing), graph algorithms, advanced statistics, or basic concepts and practices of DevOps is a real plus.
Responsibilities
• Develop working software and artifacts to create high performance and adaptive data repositories and associated retrieval frameworks required to manage a continuously updated product data library
• Design and refactor as necessary to maintain clean architectures and high code quality as features evolve
• Espouse OMNI’s values and culture with pragmatism and resolve:
o Customer centricity
o Business sensibility
o Platform quality software
o Ownership of results
o Continuous self and team improvement
o Candor with respect
o Lead by example
Required Skills
• Python with emphasis on Data Science (Pandas/SciPy/NumPy a real plus)
• AWS hosting (auto scaling, monitoring, cloud security, reliability engineering)
• Portability technologies Containers (Docker/Kubernetes), infrastructure scripting (e.g. Chef/Puppet/Ansible)
• PostgreSQL (familiarity with NoSQL technologies a real plus)
• 3+ years development experience in problem areas where the above technologies are applicable
How Success Will Be Measured
Acknowledging the potential arbitrariness of quantitative KPIs and the reality of how quickly assumptions change; business appropriate achievement of the following platform design goals will define success for the Software Development Engineer:
• Complexity Management – Systems must be as simple as possible and no simpler. “A designer knows he has achieved perfection not when there is nothing left to add, but when there is nothing left to take away. – Antoine de Saint-Exupery
• Design Pragmatism – Balanced use of modeling, formal analysis, prototyping and refactoring to achieve and maintain system simplicity (For example, by achieving strong separation of concerns and localization of state.)
• Technology Portfolio Management – Complexity in the technology portfolio presages system complexity, ergo we seek to keep our portfolio as small and duplicate-free as practicable without sacrificing our ability to achieve OMNI’s design goals.
• DevOps Practices Management – The technical infrastructure must not discourage interdisciplinary collaboration. Indeed, we desire a substrate that will preserve a DevOpos milieu as OMNI grows.
Technical and business management will assess achievement of these goals.
About OMNI Retail Group
OMNI Retail Group solves the “product discovery” problem for shoppers frustrated by purveyor websites that assume their shoppers are product experts. OMNI’s Sidekick Product Discovery Platform™ delivers an engaging and coherent shopping experience across every channel including in-store, through the call center, and via the web, kiosks, or any mobile device. Sellers enjoying the benefits of Sidekick include Walmart, Home Depot, Costco, Staples, Toys-R-Us, Dell, HP and many others. Additional background can be found in a short write-up by our CTO.
OMNI is in the early stages of a 12 to 18 month project to create a “Library of Congress” of the world’s performance product data, along with the supporting systems necessary to maintain on-going completeness and accuracy. In addition to traditional ETL tasks, this work will require collaboration with experts in Natural Language Processing, Statistics and Machine Learning, and Behavioral Economists to develop scalable automation to manage evolving product assortments, their taxonomic relationships, and metadata such as usage and market sentiment.
Meta Data
• Location: Seattle, WA
• What We Offer
o An ambitious start-up environment with a vision and strategy to create something BIG
o A competitive compensation package
• Medical, dental, and vision benefits covered 100%
• Stock Option Plan
o Flexible hours and vacation policy
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