Senior Software Engineer

About Saarthee: Saarthee is a Global Strategy, Analytics, Technology and AI consulting company, where our passion for helping others fuels our approach and our products and solutions. Our diverse and global team work with one objective in mind: Our Customers’ Success. At Saarthee, we are passionate about guiding organizations to wards insights fueled success. That’s why we call ourselves Saarthee–inspired by the Sanskrit word ‘Saarthi’, which means charioteer, trusted guide, or companion. Cofounded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA with office in UK and India. Position: Golang Engineer/Senior Engineer Location: Bangalore Work Mode: Hybrid Min-Max Experience: 6-8 years Position Summary: We are looking for a senior engineering leader to design and develop robust, event-driven microservices in Go , focused on managing high-volume, real-time financial transactions and data flows. The role will architect scalable event pipelines, integrate AI/ML into financial automation, and drive enterprise-wide system integration while ensuring compliance, resiliency, and future-ready solutions. Your Role Responsibilities and Duties: Design & Build: Develop and maintain robust, event-driven microservices in Go to support high-volume, real-time data processing and business workflows. Scalability & Reliability: Contribute to the design and improvement of event pipelines (Kafka or similar), ensuring they are reusable, extensible, and performant. Cross-Functional Collaboration: Work closely with engineering peers, product managers, and business teams to deliver solutions that are resilient, compliant, and aligned with requirements. Real-Time Data Processing: Implement and optimize streaming solutions (Kafka or equivalent) to enable real-time insights and responsiveness. Data & Database Management: Write efficient SQL queries, optimize data models, and work with both relational and NoSQL databases for performance and scalability. Cloud & Infrastructure: Deploy, monitor, and manage services on AWS (or other cloud platforms), using automation tools (Terraform, CI/CD pipelines) to streamline delivery. Continuous Improvement: Enhance system performance, reliability, and security through proactive monitoring, testing, and refactoring. Learning & Growth: Stay up to date with modern engineering practices (observability, container orchestration, DevSecOps) and contribute ideas to improve the team’s technical capabilities. Required Skills and Qualifications: Mandatory: Professional Experience: 6-8 years of software engineering experience, with solid exposure to building distributed systems or event-driven applications. Golang Proficiency: Strong hands-on experience in Go (Golang), with the ability to design, implement, and optimize microservices handling real-time or large-scale data processing. Event Streaming: Working knowledge of Kafka (preferred) or similar event-streaming platforms, including developing and maintaining data pipelines for real-time processing. Databases: Proficiency in SQL and experience working with relational databases (e.g., PostgreSQL, MySQL) and at least one NoSQL or modern data platform (e.g., MongoDB, Redis, Snowflake). Cloud Platforms: Hands-on experience with AWS (preferred) or other major cloud providers, including deploying and operating services in production environments. Infrastructure as Code: Exposure to Terraform, CloudFormation, or similar tools for automating infrastructure provisioning and management. CI/CD Pipelines: Experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI for automating build, test, and deployment workflows. Collaboration & Ownership: Ability to work independently while being an active team player, with strong problem-solving skills and accountability for delivering reliable and scalable solutions. Nice to Have: Familiarity with financial operations automation (e.g., reconciliations, settlements, reporting) or willingness to learn domain-specific workflows. Knowledge of container orchestration platforms like Kubernetes and service mesh patterns. Experience in observability tools (Prometheus, Grafana, ELK, Open Telemetry) for monitoring and troubleshooting distributed systems.