Terakeet

Enterprise marketing partner for Fortune 500 brands seeking meaningful connections and growth.

Senior Backend Software Engineer, Python

Backend EngineerSoftware EngineerFull TimeRemoteTeam 201-500H1B SponsorCompany SiteLinkedIn

Location

Arizona + 5 moreAll locations: Arizona, Illinois, New York, North Carolina, Minnesota, Texas

Posted

28 days ago

Salary

$127K - $192K / year

8 yrs expEnglishAWSCloudCypressDjangoDockerGraph QLJavaPythonRDBMSRuby

Job Description

• Designing, building, and maintaining backend services and APIs using Python and related frameworks. • Ensuring database architecture, data flow, and system performance scale effectively with growing demand. • Applying strong database fundamentals to real-world systems, including indexing strategies, partitioning approaches, and concurrency considerations for large and complex datasets. • Advocating for best practices in code quality, system design, and documentation, including participation in code reviews and architectural discussions. • Collaborating with the team to standardize processes and improve long-term maintainability of backend systems. • Evaluating and responsibly leveraging AI-assisted development tools while adhering to sound engineering principles (e.g., SOLID, single-responsibility design). • Contributing to a culture of testing, reliability, and continuous improvement.

Job Requirements

  • 8–10 years of professional software development experience.
  • Expert-level proficiency in one or more enterprise-level backend languages such as Python, Ruby, Java, or C#, with a strong preference for Python and Django.
  • Deep, practical knowledge of relational databases (RDBMS), independent of a specific engine.
  • Ability to reason about and design systems that handle millions of rows and complex data relationships.
  • A strong architectural mindset with demonstrated experience building maintainable, well-documented systems.
  • Experience building and optimizing REST and/or GraphQL APIs in high-concurrency, data-intensive environments.
  • Familiarity with containerized and cloud-native infrastructure, including Docker and managed database services such as AWS RDS, Snowflake, or equivalent platforms.
  • A consistent practice of writing, maintaining, and documenting automated tests, including unit and integration testing (e.g., Pytest, Vitest, Cypress).

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