Afresh

Full-stack Engineer

• Build and maintain robust data pipelines that ingest, transform, and validate complex customer data using PySpark, Python, and dbt to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use.
• Help improve integrations with new customers, making the process faster and more repeatable through thoughtful tooling.
• Contribute to the adoption of cutting-edge AI tooling (e.g., LLM-assisted data cleaning, semantic validation, and anomaly detection).
• Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features.
• Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations.
• Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need.
• Learn and grow by pairing with other engineers, participating in design reviews, and taking on bigger and bigger projects.

Software Engineer, Data

• Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data.
• Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use.
• Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs.
• Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features.
• Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations.
• Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need.
• Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback.

Senior Software Engineer, Data

• Deliver a project that helps generalize model configuration, enables no-code model deploys, or improves integration testing across ML systems.
• Own the design and implementation of significant scalability improvements and additions to the ML platform.

Senior Software Engineer, ML Platform

• Own and deliver infrastructure projects end-to-end, from problem definition and technical design through implementation, rollout, and iteration
• Build and improve platform primitives for service teams to deploy and debug their services
• Improve observability and operational readiness to detect issues early and reduce recovery time
• Identify and implement cost and performance improvements across cloud infrastructure
• Work closely with Security to implement practical security controls
• Participate in on-call rotation and improve monitoring and alerting

Software Engineer, Data

Senior Software Engineer, Data

Senior Software Engineer, Data

Software Engineer, Data

Senior Software Engineer, ML Platform

Senior Software Engineer, Infrastructure