Senior Software Engineer, Data
Afresh Technologies, Inc.
About the role
About
Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting‑edge technology. Our best‑in‑class AI research has been published in top journals including ICML, and we've raised over $148 million in funding from investors including former co‑CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors.
Fresh is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Responsibilities
- 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.
Requirements
- Significant experience designing and maintaining ETLs that process large‑scale datasets.
- Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
- Strong problem‑solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
- A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
- Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
- A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
- Excellent communication skills—you’re able to explain your ideas clearly to both technical and non‑technical audiences.
- Proven leadership in technical projects, with a willingness to mentor and help others grow.
We encourage all highly‑qualified candidates to apply, even if they don’t meet every listed qualification.
Why Work Here
- Join a mission‑driven company reducing millions of pounds of food waste in grocery stores per year.
- Work on challenging, real‑world problems that have a direct impact on our customers.
- Be part of a collaborative, supportive team where your ideas are valued and acted on.
- Use cutting‑edge tools and platforms to solve meaningful data challenges.
Salary
Salary Range in Canada (CAD): $137,000 - $185,000
Additional Information
- This position is not eligible for immigration sponsorship.
- Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
Requirements
- Significant experience designing and maintaining ETLs that process large-scale datasets.
- Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
- Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
- A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
- Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
- A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
- Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences.
- Proven leadership in technical projects, with a willingness to mentor and help others grow.
Responsibilities
- 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.
Skills
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