Senior Software Engineer EW II

Accountabilities

Own end-to-end engineering delivery: Lead the development and delivery of backend features, platform modules, and technical initiatives, from initial requirements and design through implementation, deployment, and production support.
Develop scalable backend services: Design, build, and maintain production-ready Python applications and REST APIs using modern frameworks such as FastAPI, Flask, and Quart.
Build distributed data platforms: Develop and optimize large-scale data processing pipelines using PySpark and SQL to support complex enterprise data operations.
Design data ingestion frameworks: Create and enhance scalable ingestion solutions capable of processing structured and semi-structured data from enterprise APIs, databases, cloud storage, and multiple file formats.
Optimize platform performance: Drive improvements in scalability, reliability, observability, maintainability, and processing efficiency across backend services and distributed systems.
Translate business requirements into technical solutions: Collaborate with product managers, architects, and technical leads to understand business needs and develop robust, scalable engineering solutions.
Coordinate engineering initiatives: Break down complex projects into manageable deliverables, estimate development effort, identify technical risks, and support timely execution across engineering teams.
Promote engineering excellence: Conduct code reviews, establish development best practices, and contribute to technical design discussions while mentoring junior engineers.
Manage production troubleshooting: Investigate complex technical issues, perform root cause analysis, and implement improvements that strengthen system stability and reliability.
Drive innovation and continuous improvement: Adopt modern engineering tools, AI-assisted development practices, and emerging technologies to improve productivity, code quality, debugging, and problem-solving.
Requirements:
4–6 years of professional experience in backend software engineering or data engineering, preferably within a scalable B2B SaaS or data-intensive product environment.
Strong programming proficiency in Python, with proven experience developing scalable backend applications and production-grade services.
Hands-on experience designing and implementing distributed data processing pipelines using PySpark.
Advanced SQL skills, including complex query development, query optimization, and relational database design.
Strong experience building REST APIs and Python web services using frameworks such as FastAPI, Flask, or Quart.
Practical experience developing scalable ETL/ELT pipelines and enterprise data ingestion frameworks.
Experience working with cloud platforms, particularly Microsoft Azure (preferred) or AWS.
Familiarity with Git, CI/CD pipelines, version control, and modern software engineering practices.
Strong debugging, performance optimization, analytical thinking, and problem-solving capabilities.
Demonstrated ability to independently manage and deliver features, modules, or engineering projects from requirements gathering through production deployment.
Ability to estimate technical effort, identify potential risks, prioritize tasks, and ensure timely delivery.
Excellent communication and collaboration skills, with a strong sense of ownership and accountability when working with cross-functional and distributed teams.
Comfortable using AI-assisted development tools such as GitHub Copilot, Cursor, ChatGPT, and Claude to improve engineering efficiency, code quality, debugging, and technical problem-solving.
Preferred qualifications:
Experience working in B2B SaaS, supply chain technology, compliance, or other data-intensive product environments, ideally within a high-growth organization.
Knowledge of supply chain operations, compliance processes, or risk management systems.
Experience with modern cloud data platforms such as Databricks (preferred), Snowflake, and Lakehouse architectures, including Delta Lake.
Strong understanding of scalable backend architectures, distributed systems, and enterprise software design principles.
Exposure to additional technologies such as Java, Kafka, Redis, Apache Airflow, or Kubernetes.
Previous experience mentoring software engineers and contributing to architectural decisions and technical design discussions.
Benefits:
Fully remote working arrangement, offering flexibility to work from India.
Comprehensive benefits package covering health, financial wellbeing, and overall wellness.
Opportunities to connect and collaborate with colleagues through in-person team activities and events.
Meaningful ownership of technical projects and the opportunity to influence product and platform development.
Exposure to advanced technologies, including agentic AI, distributed data platforms, and modern cloud infrastructure.
Opportunities for continuous technical development and professional growth.
Collaborative and empowering work culture that encourages innovation, accountability, and knowledge sharing.
Opportunity to contribute to technology addressing critical global supply chain challenges across industries such as life sciences, pharmaceuticals, aerospace, high technology, and automotive.