Senior Data Engineer (Python/SQL)

Location: Lehi, Utah, United States; hybrid workplace

Company

hirify.global is a global technology company working with major ecommerce marketplaces including Walmart.com, Target.com, eBay, Tmall, TikTok Shop, JD, and Mercado Libre.

What you will do

• Design and implement robust ETL/ELT pipelines using Airflow, dbt, and cloud-native architectures.
• Write production-grade Python for data orchestration, processing, and tooling.
• Build and optimize complex SQL queries and dimensional models for OLAP and OLTP systems.
• Ingest and harmonize data from dozens of global marketplaces in collaboration with cross-functional teams.
• Build and maintain infrastructure-as-code and containerized workflows to improve platform reliability.
• Use AI thoughtfully to optimize processes and workflows.

Requirements

• 7+ years of professional data engineering experience focused on ETL/ELT and data modeling.
• 5+ years of expert-level SQL experience, including window functions, CTEs, and performance tuning.
• 4+ years of professional Python development for data pipelines and tooling.
• 3+ years of experience building or optimizing large-scale data warehouses such as Snowflake, BigQuery, or Redshift.
• Proficiency with Apache Spark, Trino, Kafka, and Debezium, plus experience handling petabyte-scale datasets.
• Bachelor’s degree in Computer Science, Data Science, or a related technical field, or equivalent experience.

Nice to have

• Expertise in AWS services including Terraform, EKS, and Lambda.
• Experience with Apache Iceberg or Delta Lake.
• Background in real-time streaming with Kafka or Kinesis.

Culture & Benefits

• Collaborate with Data Scientists, Software Engineers, AI Engineers, Product Managers, Marketing, and Sales.
• Work with technical leadership and AI experts across a growing, geographically distributed team.
• Contribute to major architectural changes and long-term lakehouse integration plans.
• Access continuous learning opportunities involving Apache Iceberg and real-time streaming architectures.
• Career progression toward Staff Data Engineer or specialized technical leadership roles.

Hiring process

• Phone interview with Talent Acquisition.
• Video interview, onsite interview, and executive review.
• Offer after successful completion of the interview process.