Engineering Manager (Data)

We are looking for an experienced manager 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 an Engineering leader you will lead a team of high-performing engineers to build scalable, low-latency, and fault-tolerant systems. Your team will power advanced analytics, AI/ML, and decision-making across the organization.

You will play a critical role in shaping Razorpay s data architecture, fostering a high-performance culture, and delivering solutions that support millions of users and businesses

• Lead with Vision: Define the strategy and roadmap for Razorpay s data platform, ensuring it aligns with business and technology goals.
• Team Leadership: Build, mentor, and grow a high-performing engineering team by fostering a collaborative, open, and learning-oriented culture.
• Architect Scalable Systems: Design and implement fault-tolerant, high-availability distributed systems for data ingestion, processing, and analytics.
• Collaboration: Work closely with product, business, and data science teams to identify requirements, set priorities, and build solutions that matter.
• Hands-On Contribution: Step into coding when needed to solve complex problems or provide architectural guidance.
• Operational Excellence: Establish and advocate for best practices in software development, deployment, monitoring, and incident management.
• Foster Innovation: Drive initiatives to adopt new technologies and continuously improve Razorpay s data platform capabilities.
• Ownership: Take end-to-end ownership of projects, ensuring quality, scalability, and timely delivery.

Experience: 8+ years of professional experience in software/data engineering, with at least 2+ years managing high-performing teams.

Technical Expertise:

• Proficiency in building and operating large-scale distributed systems.
• Familiarity with ETL and Analytical Platform and event-driven architectures.
• 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).

Leadership Skills:

• Proven ability to inspire and lead teams while fostering a culture of accountability and excellence.
• Exceptional leadership skills with a proven ability to mentor engineers, lead projects, and work cross-functionally.
• Experience in performance management, hiring, mentoring, and coaching engineers.
• Strong collaboration skills with cross-functional teams and stakeholders.

Soft Skills: Exceptional communication, decision-making, and problem-solving abilities.

Nice-to-Have:

• Experience with AI/ML platforms, financial systems data platforms.