Staff Software Development Engineer at Razorpay Software Private Limited

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

09 Feb, 26

Salary

0.0

Posted On

11 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Platform Engineering, Distributed Systems, Cloud Solutions, Python, Scala, Golang, SQL, Kafka, Spark, Airflow, Flink, AWS, GCP, Azure, MLOps, Data Governance, Leadership

Industry

Software Development

Description

Razorpay was founded by Shashank Kumar and Harshil Mathur in 2014. Razorpay is building a new-age digital banking hub (Neobank) for businesses in India with the mission is to enable frictionless banking and payments experiences for businesses of all shapes and sizes. What started as a B2B payments company is processing billions of dollars of payments for lakhs of businesses across India. We are a full-stack financial services organisation, committed to helping Indian businesses with comprehensive and innovative payment and business banking solutions built over robust technology to address the entire length and breadth of the payment and banking journey for any business. Over the past year, we've disbursed loans worth millions of dollars in loans to thousands of businesses. In parallel, Razorpay is reimagining how businesses manage money by simplifying business banking (via Razorpay X) and enabling capital availability for businesses (via Razorpay Capital). Location: Bangalore The Role: We are looking for an experienced Staff Data Platform Engineer to own the strategy and execution of complex data initiatives across the organization. In this role, you will drive the architecture and roadmap of large-scale data platforms, ensuring alignment with business goals. As a technical leader and subject matter expert, you will work closely with engineering and leadership teams, mentor peers across teams, and help establish the engineering excellence needed to deliver next-generation data products. Roles and Responsibilities: Architect and oversee the design of cloud-native data infrastructure and platforms that scale across multiple business units. Develop technical roadmaps for data pipelines, analytics infrastructure, and real-time processing systems. Collaborate with engineering, product, and leadership teams to align technical solutions with business strategy. Guide and mentor other engineers across the organization, fostering a culture of excellence in engineering practices. Design and implement MLOps pipelines to streamline model deployment, versioning, and monitoring. Ensure data security, privacy, and governance are embedded across all layers of the platform. Evaluate and introduce new tools and frameworks to continually improve the platform's capabilities and efficiency. Represent the team in architecture reviews, executive meetings, and external technical forums. Mandatory Qualifications: 10+ years of experience in data platform engineering or distributed systems with a focus on scalable cloud solutions. Expertise in Python, Scala, Golang, and SQL, with deep knowledge of distributed data systems. Proven ability to design real-time and batch pipelines using Kafka, Spark, Airflow, and Flink. Extensive experience working with cloud platforms (AWS, GCP, Azure) and tools like Terraform, Kubernetes, and Docker. Strong knowledge of MLOps frameworks (MLflow, TFX) and data governance tools (DataHub, Amundsen). Exceptional leadership skills with a proven ability to mentor engineers, lead projects, and work cross-functionally. Excellent communication and problem-solving skills, with the ability to influence and guide key stakeholders. Experience in open-source contributions and working in high-growth product companies. Razorpay believes in and follows an equal employment opportunity policy that doesn't discriminate on gender, religion, sexual orientation, colour, nationality, age, etc. We welcome interests and applications from all groups and communities across the globe. Follow us on LinkedIn & Twitter

Responsibilities

The role involves architecting and overseeing the design of cloud-native data infrastructure and platforms while developing technical roadmaps for data pipelines and analytics infrastructure. The engineer will also mentor peers and ensure data security and governance across the platform.