Backend Engineer-Python

Tidal Financial Group

$110K — $130K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years building production backend services with architectural decision-making skills.
  • Deep expertise in Python, particularly for web services, data access, and asynchronous processes.
  • Strong experience with PostgreSQL and relational data modeling.
  • Proficient in API design, focusing on security and safe handling of sensitive data.
  • Solid JavaScript/Node knowledge for front-end integration and micro-services.
  • Fluent in using AI in the development lifecycle, with discernment about effective implementation of AI tools.
  • Strong engineering fundamentals including testing, CI/CD, observability, and code review.

Responsibilities

  • Design, build, and operate production Python services with clean APIs and data models.
  • Own backend development for major platform projects and establish new services as the business evolves.
  • Model and query data in PostgreSQL; design secure APIs for ease of integration.
  • Collaborate with Node/JavaScript front-ends and micro-services across the tech stack.
  • Leverage AI tools throughout design, prototyping, implementation, and code review processes.
  • Establish robust standards for a young Python codebase, including testing and code review practices.
  • Coordinate with product and compliance teams to meet regulatory software requirements.

Benefits

  • Collaborative work environment with a focus on team growth and development.
  • Opportunity to set standards and best practices in emerging technologies like Python.
  • Work on regulated financial software, ensuring your impact resonates across the organization.
  • Engagement with cutting-edge AI tools in the software development process.
Full Job Description
About the role:

This is a backend-focused role building production services in Python, with JavaScript/Node across the wider stack for front-ends and micro-services. As Tidal invests in Python as a primary backend language, you'll be a founding voice in the practice- setting the patterns, standing up the services, and helping the team grow.

Your work is the backend for the platforms and products our engineering group is buildingacross the firm. This is real, regulated financial software, where correctness, auditability, and clarity matter as much as speed.

What you'll do:

  • Design, build, and operate production Python services - clean APIs, sound data models, and sensible async - that other teams and systems depend on.
  • Own the backend for major platform projects and stand up new services as the business grows.
  • Model and query data in PostgreSQL, and design APIs that are secure and easy to build on.
  • Pair with Node/JavaScript front-ends and micro-services across the stack.
  • Work AI-native - use AI fluently across design, prototyping, implementation, and review, and help raise the bar for how the whole team works.
  • Set the standard for a young Python codebase: testing, CI, code review, and the conventions others will follow.
  • Partner with product and compliance to turn regulated, real-money requirements into software people trust.

Qualifications:

  • 5+ years building and running production backend services (not just scripts), with the judgment to make architecture calls and keep a codebase healthy.
  • Deep Python expertise across web services, data access, and asynchronous work.
  • Strong PostgreSQL and relational data modeling.
  • Solid API design and security - authn/authz, input validation, and safe handling of sensitive data.
  • Strong JavaScript / Node - comfortable across front-end integration, micro-services,and the glue between systems.
  • Fluent using AI in design and development. You already design, build, and review with AI tools and have judgment about where they help and where they don't - central to how we work.
  • Sound engineering fundamentals: testing, CI/CD, observability, and code review as habits.

Preferred skills:

  • ETF or asset-management domain knowledge.
  • Market-data platforms (e.g., Bloomberg).
  • AWS, containers, and infrastructure-as-code.
  • Snowflake or other data-warehouse and pipeline experience (Parquet/DuckDB a plus).
  • TypeScript/React on the front end.

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