Software Engineer - Backend

Overview

SkillCorner provides physical and tactical performance data for professional sports teams and leagues. The Backend team builds and maintains the systems that power SkillCorner's products, working closely with the Product team. The stack is primarily Python (Django, FastAPI), AWS , PostgreSQL , Redshift and ClickHouse . The team covers services, APIs, schema design, and operations tools. Each developer owns specific domains while contributing across projects.

Responsibilities

• Develop and maintain high-impact features for clients and internal teams.
• Drive technical and architectural decisions.
• Ensure overall code quality (tests, best practices, reviews).
• Share your knowledge and mentor junior developers to help them grow.
• Client APIs: design, maintain, and scale the APIs that deliver data to clients and internal consumers.
• Data ingestion & provider integration: integrate and reconcile sports data from multiple third-party providers, handle schema design for competition-specific rules, and ensure data consistency across sources.
• Operations tooling: centralized internal platform for managing matches, line-ups, data validation, and operational workflows used daily by the ops team.
• Multi-sport expansion: extend the platform to new sports (basketball and beyond) with new data models, APIs, and pipelines adapted to each sport's specificities.
• Service architecture: design and build backend services as part of an ongoing effort to decompose a monolithic platform into well-scoped, independent services.
• Shared libraries & developer experience: maintain core Python libraries (utilities, models, HTTP clients) used across the company, and drive code quality improvements (testing, refactoring legacy code, tooling).

Must have

• 5+ years of experience in software engineering.
• Strong expertise in Python and backend development.
• Ability to drive technical decisions and justify them.
• Solid understanding of distributed architectures, databases, and data modeling/schema design.
• Experience with a Python web framework (Django, FastAPI, or similar).
• Solution-oriented mindset, eagerness to learn and to share knowledge.

Nice to have

• Experience with cloud environments (preferably AWS).
• Knowledge of analytical databases (Redshift, BigQuery, ClickHouse, ...).
• Experience with data processing libraries such as pandas or polars.
• Experience with data quality challenges, such as duplicates, consistency checks, or merging records from multiple sources.
• Experience with service-oriented architectures and splitting monolithic systems.
• Familiarity with IaC tools (Pulumi, Terraform).
• Interest in sports or sports analytics.