About the role

You’ll be a key member of our Core Data Engineering team. You’ll be owning changes to our common code and standard schemas to fit the company’s product needs (i.e. new products and features), and creating tools to help increase our customer integration velocity. If you’re interested in building software to support our mission, we hope you’ll join us!

• Design, build, scale, and deploy fast and reliable ETL pipelines in Python, Pandas, Spark, SQL, and DBT, - across our data platforms (powered by Databricks, Postgres, Snowflake, and Delta Lakes) - to process billions of data points from US retail stores and to power our recommendation engine and ordering system
• Collaborate with an interdisciplinary team of experts in Go-To-Market, machine learning, data science, product, and product engineering to understand how to properly transform customer data and to implement solutions
• Monitor and analyze data, and work with internal stakeholders to either create dashboards, clearly escalate high-priority issues back to the customer, or find novel workarounds to extract the signal we need from customer data
• Develop standard tools that help increase the velocity at which we can integrate new customers and release new product features

Skills and experience

• Ability to identify a problem or area of improvement, design, solution, and see it through to implementation
• Strong understanding and experience with various data stores (databases, data warehouses, key/value stores, etc.). Experience with Apache Spark, Pandas, SQL, or other Big Data frameworks and cloud infrastructure preferred
• Experienced with architecture & design of data driven solutions
• Strong problem-solving ability and ability to work through ambiguity and incomplete specifications
• Dedication to code quality, testing, design processes, automation, and operational excellence
• An active stakeholder in engineering tools discussions and help us build and design for future growth
• Excellent written communication, verbal communication, and collaboration skills

The following represent the skills and experience our ideal candidate possesses. We encourage candidates to apply, even if they do not fulfill all the listed criteria.

Afresh is committed to pay equity and providing highly competitive cash compensation, equity, and benefits package. Afresh conducts a pay equity audit twice each year to ensure that jobs of similar scope and impact are paid similar amounts. The final compensation offered for this role will be based on multiple factors such as the role’s scope, complexity, internal equity, the candidate’s experience/expertise, and success through the interview process.

Salary Band:

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