Staff Software Engineer - Core Data Engineering

The job overview for this role at Afresh is located towards the beginning of the job description and is labeled "About the Role". As a member of the Core Data Engineering team, the ideal candidate will be responsible for designing, building, scaling, and deploying ETL pipelines in Python, Pandas, Spark, SQL, and DBT to process billions of data points from US retail stores. They will also collaborate with an interdisciplinary team to properly transform customer data and implement solutions, monitor and analyze data, and develop standard tools to increase customer integration velocity. The ideal candidate should possess strong problem-solving ability, dedication to code quality, testing, design processes, automation, and operational excellence, and excellent communication and collaboration skills.

• Design, build, scale, and deploy fast and reliable ETL pipelines in Python, Pandas, Spark, SQL, and DBT, across data platforms to process billions of data points from US retail stores and to power recommendation engine and ordering system
• Collaborate with interdisciplinary team of experts 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
• 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

• Design, build, scale, and deploy fast and reliable ETL pipelines in Python, Pandas, Spark, SQL, and DBT, across data platforms to process billions of data points from US retail stores and to power the 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 needed from customer data
• Develop standard tools that help increase the velocity at which new customers can be integrated and new product features can be released
• 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 build and design for future growth
• Excellent written communication, verbal communication, and collaboration skills