Rewards Network

Rewards Network

Senior Scala Engineer (Hybrid)

Chicago, IL · Senior · Full-time

Sponsorship not specified$130k-$170kDetected 6 days ago
ScalaDockerKubernetesCI/CDRESTKafkaData AnalysisCybersecurityCollaboration

About the role

  • About Rewards Network For 41 years, Rewards Network has been helping restaurants grow revenue, increase traffic, and boost customer engagement through innovative financial, marketing services, and premier dining rewards programs.
  • We're open to hiring at the mid to senior level based on experience.
  • This is a hybrid position that requires in office presence 3 days a week (Tuesday-Thursday) in Chicago.

Responsibilities

  • By offering unique card-linked offers, we introduce diners to fantastic restaurant experiences, leveraging advanced technology and data analytics to deliver value to restaurants, diners, and our strategic partners' loyalty programs.
  • Our engaging and rewarding environment is designed to help you gain your full potential.
  • The Software Engineer builds and evolves back-end systems that power client-facing web applications, delivering seamless, modern digital experiences.
  • In this role, you'll support Rewards Network's management portal and dining platform by developing scalable, secure features that improve the experience for millions of users and thousands of restaurant partners.
  • We encourage and strongly support workplace diversity.

Nice to have

  • 4+ years of back-end software development experience (7+ preferred), with a strong focus on Scala and functional programming.
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience (e.g., coding bootcamp or self-taught expertise)
  • Proficiency in Scala and other JVM or functional programming languages
  • Hands-on experience with relational databases and data management best practices.
  • Familiarity with event-driven systems and streaming technologies (e.g., Kafka).
  • Experience with modern development tools and infrastructure, including Docker and Kubernetes (preferred).
  • Strong coding practices, including writing clean, testable, and maintainable code.
  • Understanding of web security principles and secure application development.

Skills

  • Write high-quality, well-tested code to ensure reliability, performance, and scalability.
  • Ensure security best practices are embedded across back-end systems and data flows.
  • Contribute to continuous improvement of development processes, tools, and best practices.

Compensation

  • Expected Pay Range
  • $130,000 - $170,000 USD

Benefits

  • Generous dining reimbursement when you dine with our restaurant clients
  • Two medical plan options- Standard PPO or High Deductible Health Plan (HSA with company match for HDHP participants)
  • Two dental plan options and a vision plan
  • Flexible Spending Accounts and a pre-tax commuter benefit program
  • Short Term and Long Term disability
  • Company-paid life insurance and AD&D insurance, supplemental employee, spouse, and child life insurance
  • including flexible PTO, 11 company holidays, and parental leave.
  • We take pride in partnering with the world's most powerful loyalty programs to drive full-price paying customers to local restaurants through marketing services and flexible funding options.

Company info

  • This is a full-time, exempt position. The base salary range for this role in Chicago is $130,000-$170,000 annually, depending on level (mid-level or senior), as well as candidate experience, skills, and other factors. This role is also eligible for an annual bonus target of 10%, bringing total target compensation to $143,000-$187,000.
  • Comprehensive benefits package, which includes:
  • Competitive Time Off
  • At Rewards Network, you'll be part of a driven and diverse team that excels in collaboration, issue resolution, and taking ownership of both personal growth and the company's success.

Equal opportunity

  • Equal Opportunity Employer (EOE).

This listing is sourced directly from Rewards Network's careers page and normalized into a canonical job model.