Data Architect

About the Open Apparel Registry

The Open Apparel Registry (OAR) is a free and open data tool mapping garment facilities worldwide and allocating a unique ID to each. The tool is used by stakeholders across the apparel sector to eliminate confusion and facilitate collaboration, enable interoperability across systems and tackle the long-standing industry problem of facility identification. We are built on the principles of "open": open data, open communications patterns, openness to ideas and new ways of working. We are a mission-driven organization and respect and value our stakeholders - they make the OAR what it is: a tool enabling collaboration across an entire sector.

The OAR is currently at an exciting period in its growth and development and is looking for a Data Architect to contribute to the definition and implementation of an open data, geospatial tool within the context of a rapidly expanding global nonprofit. Our ideal candidate is mission driven with a desire to use their data science and development skills to democratize global supply chain data and accelerate the progress towards addressing intractable issues that exist in supply chains - issues like modern day slavery and environmental degradation. Successful applicants will have the opportunity to contribute to the future growth and vision for the tool and must be prepared to “get their hands dirty” with a wide variety of tasks. We are scaling quickly and will be hiring new team members throughout 2022.

Job Description

The OAR Data Architect will be our first data team leader, tasked with developing an expanded data model, implementing a data and analytics infrastructure, managing data engineering tasks, and leading the data and ID schema strategy. The Data Architect will work closely with the OAR’s leadership team, community engagement team, product team, and contracted technical provider to:

  1. Scale our current information framework from an apparel-specific database with over 80,000 facilities to model a broader range of global retail supply chains, with the potential to identify and track millions of production and manufacturing facilities.

  2. Balance the immediate need of scaling the platform with the strategic need to position the organization as core infrastructure within the rapidly-expanding supply chain transparency / ESG ecosystem.

  3. Develop a robust but flexible data strategy to maximize future opportunities to deliver positive outcomes for our stakeholders while robustly interoperating with other components of the open supply chain ecosystem.

The position is remote, but we ask that the employee be located in the US, or be willing to align their work schedule to partially overlap with US Eastern business hours. This position can be hired as a full-time employee or as a consultancy. If full-time, benefits include medical and vision insurance and a generous parental leave and vacation policy. The OAR is a lean organization with an entirely remote staff base; this position may require travel for occasional regional meetings or annual retreats with global staff.

Deadline: May 31, 2022

Our Commitment

OAR is committed to creating an inclusive and representative environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Responsibilities

  • Review and assess the current OAR information architecture in order to identify gaps, opportunities and priorities.

  • Develop the data strategy and cross-functional thinking in how OAR’s platform and data standard drive progress and impact for the organization.

  • Develop and implement the OAR data roadmap which includes data infrastructure, data science, data model enhancement, and analytics for program impact, product performance, and data quality.

  • Lead on defining the organization’s data architecture vision and collaborate with other technical staff on the organization's overall technical vision and strategy.

  • Articulate the OAR data architecture to technical and nontechnical audiences, and communicate how OAR’s data strategy ties to the organization’s broader impact.

  • Identify opportunities to invest in data infrastructure and create robust systems that support expansion plans, and create positive outcomes for the organization and our stakeholders.

  • Longer term, manage a growing data team that supports data engineering, data science, and analytics.

  • Support the data science functions of our organization by understanding the data and developing code that manages complex data pipelines.

The Ideal Candidate

  • You are a data leader with experience in data engineering, machine learning/prediction, and analytics who knows how to effectively and strategically support existing data needs while also scaling into the future.

  • You have experience in a high growth, consumer or SaaS company and understand what it takes to build a high performing data organization. Bonus points if you have experience with GIS, ESG, or GHG accounting data or platforms.

  • You have an eye for strategies, investments, and skill sets that can accelerate the impact of our mission; and you have a demonstrated ability to turn analysis into positive outcomes for organizations.

  • You are proficient in modern data stacks, tools, languages, including SQL, Tableau, Python, R, etc.

  • You have an interest in the complexity and nuances of global supply chains and are motivated to dig in and understand how data can be leveraged to combat intractable issues that persist within them - issues like modern day slavery and environmental degradation.

  • You are excited about OAR’s mission, opportunities for growth and potential impact; you are an advocate for the power of open data.

  • You are open to a pro-feedback, pro-fun, mission driven and global workplace culture.

Must have:

  • Mastery of multi-disciplinary data roles: data engineering, data science, data analysis
  • Strong track record guiding data architecture, data pipeline, and data strategy
  • Managing data roadmap for growing organization
  • Experience with SQL, Python, and non-relational databases
  • Experience creating KPIs and overall evaluation criterion & monitoring/tracking successfully

Nice to have:

  • Experience working with supply chain/ESG/GHG data
  • AI/NLP (Natural language processing) data expertise
  • Experience with geospatial data
  • Experience in a social enterprise, B Corp or nonprofit

Benefits & Compensation

  • This role has enormous growth potential alongside the growth of the organization across geographies and sectors

  • The team is open to flexible working patterns, encouraging team members to work in the most effective way that ensures work gets done efficiently

  • Competitive salary, benchmarked against similar tech roles in the nonprofit sector

  • Medical and dental insurance

  • Professional development stipend

  • Generous vacation and parental leave

Apply:

To apply for this position, please email resume, cover letter (maximum 2 pages for each), relevant GitHub projects and other development samples to recruiting@openapparel.org with the subject line “Data Architect Application.”

Deadline: May 31, 2022

For more about the OAR:

The Open Apparel Registry

The Open Apparel Registry (OAR) is a neutral, open data tool mapping garment facilities worldwide and allocating a unique ID to each. The tool is used by stakeholders across the apparel sector to eliminate confusion and facilitate collaboration, enabling interoperability across systems and tackling the long-standing industry problem of facility identification. The power of the OAR’s approach lies in transforming messy, inconsistent data into structured datasets, made freely available to all stakeholders under an open data license. As well as many other efficiency and process benefits, the way that the OAR organizes and presents data ultimately improves the lives of some of the most vulnerable workers in global supply chains.