Senior Data Engineer (AI)

TL;DR

Senior Data Engineer (AI): Designing and implementing scalable ETL pipelines and integration tools to process large volumes of customer data for an AI-driven grocery platform with an accent on data reliability and system scalability. Focus on building robust PySpark and DBT frameworks, optimizing ETL runtimes, and solving complex data quality challenges to power machine learning solutions.

Location: Remote (Must reside in one of the following US states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI)

Salary: $156,000 - $211,000

Company

hirify.global is an AI platform for the grocery industry focused on reducing food waste through proprietary AI designed for high-volatility environments.

What you will do

• Design and implement robust ETLs using PySpark and DBT to process billions of records from customer datasets.
• Build tools and frameworks to streamline customer integrations, enabling faster onboarding and better data handling.
• Optimize ETL runtimes and improve data processing scalability to reduce integration effort.
• Collaborate with product, engineering, and go-to-market teams to deliver data solutions for new features.
• Resolve real-world data quality challenges by processing messy, incomplete, or inconsistent customer data.
• Mentor other engineers, lead technical discussions, and provide actionable feedback.

Requirements

• Significant experience designing and maintaining ETLs for large-scale datasets.
• Proficiency with Python, PySpark, SQL, and platforms such as Databricks, Snowflake, or DBT.
• Proven ability to handle complex, unclean datasets and find innovative ways to process and analyze them.
• Strong leadership skills and experience mentoring other technical team members.
• Must be based in one of the specified US states.
• This position is not eligible for immigration sponsorship.

Culture & Benefits

• Work for a mission-driven company dedicated to reducing millions of pounds of food waste.
• Tackle challenging, real-world data problems with a direct positive impact on the environment.
• Collaborative and supportive team culture where ideas are valued and implemented.
• Access to cutting-edge AI tools and platforms.