Software Engineer

What You Will Do

Develop scalable and reliable backend systems by applying distributed systems principles such as asynchronous processing, fault tolerance, and efficient resource utilization.
Develop secure applications following authentication, authorization, and secure coding best practices.
Experience developing containerized applications using Docker.
Experience using logs, metrics, and monitoring tools to troubleshoot production systems.
Experience working with relational database design, indexing, and query optimization.
Deliver high-quality engineering solutions that meet product goals while adhering to agreed timelines.
Develop and maintain backend services, distributed data pipelines, and scalable ingestion frameworks that process data from multiple enterprise sources.
Develop and maintain production-grade Python web services and well-designed, documented, and versioned REST APIs using modern frameworks such as FastAPI, Flask, and Quart to support scalable backend applications and data ingestion services.
Develop and maintain distributed data pipelines using PySpark and SQL.
Build and enhance scalable data ingestion frameworks that support structured and semi-structured data from enterprise APIs, databases, cloud storage, and multiple file formats.
Investigate and resolve production issues while proactively enhancing platform reliability, performance, and scalability.
Develop well-tested, maintainable software by embracing automated testing, code reviews, CI/CD, and comprehensive documentation.
Collaborate effectively with senior engineers and cross-functional teams.
Continuously learn and adopt new engineering tools, technologies, and best practices to improve technical expertise and contribute to engineering excellence.

What You Will Bring

2–4 years of experience in backend engineering or data engineering, preferably in scalable product environments.
Strong programming skills in Python, with experience developing backend applications, REST APIs, and data processing solutions using modern engineering practices.
Hands-on experience building distributed data processing pipelines using PySpark, along with strong SQL skills, including writing complex queries, query optimization, and working with relational databases.
Experience building backend services and working with cloud platforms such as Microsoft Azure (preferred) or AWS.
Hands-on experience with Git and modern version control practices.
Strong problem-solving and debugging skills, with the ability to take ownership of engineering deliverables and independently drive solutions with minimal guidance.
Growth mindset with a passion for learning, continuous improvement, and thriving in a collaborative product engineering environment.
Effectively leverage AI-assisted development tools while applying sound engineering judgment and maintaining high standards for code quality, correctness, and security.

What Will Make You Stand Out

Experience working in a B2B SaaS, supply chain, compliance, or other data-intensive product company, preferably in a high-growth environment.
Exposure to supply chain operations, compliance, or risk management domains.
Exposure to modern cloud data platforms such as Databricks (preferred), Snowflake, and Lakehouse technologies including Delta Lake.
Experience building scalable ETL/ELT pipelines and data ingestion frameworks.
Exposure to one or more of the following technologies: Java, Kafka, Redis, Apache Airflow, or Kubernetes.