Environmental Impact Analytics Engineer

As the Environmental Impact Analytics Engineer, you will be responsible for building, maintaining, automating, and improving data systems and tools that track Patagonia’s progress towards its product specific environmental goals. This will include incorporating new and existing product and materials specific environmental impact data into automated analytics systems. You will be responsible for maintaining and enhancing the backend data infrastructure associated with Patagonia’s Environmental Profit & Loss tool (EP&L). In this role, you will work closely with stakeholders from across the company, which include advising business teams on the environmental impacts of our fiber selection and product creation process. You will partner closely with the Supply Chain and Corporate Environmental Impact Sr. Analyst on the maintenance of shared data sources, the creation of complementary impact data tools, curation, and presentation of context rich insights to key stakeholders. As the Environmental Impact Analytics Engineer, you will have a hand in scaling our product environmental impact analytics to further promote a data-driven culture while reducing impacts from Patagonia products and materials.

What You’ll Do

Data Management:

Manage materials, product styles and trim use quantification and environmental impact data and reporting.
Execute data management processes including timely and accurate data collection from key internal and external data sources, validation, and analysis.
Prototype and continuously improve data models, reports, and dashboards.
Lead project QA, validation, and data quality process.
Partner with Centralized Data and Reporting team to implement enterprise best practices with opportunity to create predictive analytics and AI models.
Partner with the Supply Chain and Corporate Environmental Sr. Analyst on the development and maintenance of complementary environmental impact tools that provide a holistic view of impact across the Patagonia value chain.
Maintain long term materials and product data storage strategy using Snowflake.
Create and maintain process documents related to data architecture and processes

Develop and Improve Data Systems:

Design build, deploy, optimize, and evolve data models to support the environmental impact team.
Incorporate new sources of data into existing data systems.
Support processes to improve transparency and automation around data quality, readiness, and performance.
Create and automate the ability to compare product and material environmental impacts to future hypothetical impacts.
Standardize process and tools to capture, integrate and manage data and ensure data quality.

Data Analysis:

Identify trends and overarching data insights for key business owners.
Complete ad hoc material and product environmental data requests.

Reporting and Communication:

Develop and implement automated environmental product reporting efforts including Environmental Profit and Loss (EP&L) scoring.
Ensure material and product environmental data and dashboards are created for leadership and other key internal stakeholders.
Partner with the Supply Chain and Corporate Environmental Sr. Analyst to deliver end-to-end analytics, from understanding the business challenges to presenting insights to leadership through data visualization and storytelling.

Who You Are

Data Expert – comfortable reading, manipulating, and communicating about data
Self-Directed – able to work well under pressure and deadlines
Active Learner – constantly seeking ways to understand data problems and envision solutions
Results Driven – able to tie your expertise to tangible solutions and outcomes
Strategic – quickly able to identify the “why” despite competing priorities and complex, layered problems
Influencer – ability to influence and educate with a collaborative spirit and a creative, open mind

Experience You Bring

Bachelor’s Degree in Computer Science, Supply Chain Management, Engineering, Information Systems, Analytics, Mathematics, or other relevant subject matter, or equivalent in ongoing self-education and work experience of approximately 3+ years.
3+ years of experience in data engineering, data analytics, data science or related field.
3+ years of full-time complex project management experience coordinating and prioritizing multiple work streams to achieve strategic objectives.
Highly proficient in SQL and Python.
Experience with automated data transformation tools such as dbt.
Experience using cloud-based data warehousing such as Snowflake.
ELT/ETL tool experience (Fivetran, Stitch, Hightouch, Census, Matillion, etc.).
Proficiency in business intelligence/data visualization tools such as Tableau.
Experience using Airtable.
Strong proficiency in developing queries in a business environment with large-scale, complex data sets.
Proficiency in data transformation, modeling methodology and data orchestration tools.
Experience with database systems and architecture.
Familiarity/experience with large-scale enterprise software.
Familiarity/experience with Higg MSI, LCA and other environmental impact datasets and tools a nice to have.

Pay range: $91,872-$153,120‍

Hiring range: $105,000-$125,000.

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