Skip to main content

Perpay - Career's Page

Data Engineer

Philadelphia, Pennsylvania, United StatesmidAdded 1 month ago

About this role

Perpay is seeking a Data Engineer to enhance their data infrastructure in Philadelphia, focusing on real-time event ingestion and AI-assisted workflows. The ideal candidate will have experience in production data engineering and a collaborative spirit to solve complex business problems.

What you'll do

  • Develop and maintain data pipelines
  • Enhance real-time data ingestion processes
  • Redesign risk decisioning services
  • Collaborate with engineering, risk, and finance teams
  • Document and maintain code for production
  • Support the analytics and data science teams

What they're looking for

  • Experience in data engineering (2+ years)
  • Proficiency in Python and SQL
  • Familiarity with AWS services
  • Knowledge of data pipeline design
  • Understanding of orchestration tools like Airflow
  • Experience with data warehousing tools like Redshift
  • Strong documentation and stakeholder communication
  • Comfortable with infrastructure-as-code practices

Benefits

  • Collaborative office environment
  • Flexible work arrangements
  • Career growth opportunities
  • Focus on meaningful financial impact
  • Generous perks and benefits
  • Engaging team culture
Apply with Autofill

Opens the application — the Jobs AI extension fills it for you. Set up autofill

Opens the official application on the employer’s site. No login required.

Perpay - Career's Page

Perpay builds financial solutions designed to improve financial stability for consumers with subprime credit. The company is hiring Software Engineers at various levels and Data Engineers to develop features, enhance products, and build data infrastructure in Philadelphia.

Website
perpay.com
View all jobs at Perpay - Career's Page

Likely interview questions

  • Walk us through a data pipeline or platform you designed in a previous role—what were the key trade-offs you made, and what would you do differently today?
  • Tell us about a time when data quality issues made it to production. How did you identify it, fix it, and prevent it from happening again?
Unlock all 7 questions free — and practice them live →