Senior Software Engineer

As a Senior Software Engineer in the Cleanroom team, you will be driving delivery, and execution for critical data systems. You will define engineering standards, implement the best practices, mentor junior engineers, and ensure the Cleanroom platform scales securely and reliably to support sustained business growth. What will you do?

• Deliver large-scale cloud-native data platforms primarily on AWS using Databricks and distributed processing frameworks to build highly scalable and resilient systems.
• Work hands-on across the technology stack - including Python, PySpark, Apache Spark, Databricks, AWS services, event-driven architectures, and SQL/NoSQL databases - to solve complex engineering challenges and maintain platform excellence.
• Partner closely with global engineering, product management, architecture, and business partners to align technical solutions with strategic business objectives.
• Own the end-to-end software development lifecycle, including requirements gathering, solution design, development, deployment, observability, and documentation.
• Design and develop reusable, maintainable and scalable components and actively participate in the architecture discussions, technical design reviews, code reviews.
• Mentor and guide junior engineers, fostering a culture of innovation, accountability, collaboration, and technical excellence.

• B.E/B.Tech/M.Tech/MCA in Computer Science, Information Technology or a related field.
• 5-8 years of strong software engineering experience, with significant expertise in large-scale data engineering and distributed systems architecture.
• Experience in Data Warehousing, Data Lakes, Delta Lake architecture, and modern big data ecosystem designs.
• Deep hands-on expertise in Databricks, Python, PySpark, and Apache Spark, with proven experience building high-performance distributed data processing solutions.
• Strong experience with AWS services such as S3, Glue, Athena and Lambda for building scalable and reliable cloud-native data platforms.
• Experience with messaging technologies such as Kafka and RabbitMQ, along with strong expertise in relational and NoSQL databases including SQL Server and MongoDB.
• Experience implementing robust testing strategies, including unit, integration, and regression testing, while adhering to engineering best practices.
• Strong understanding of CI/CD and DevOps practices using tools such as Jenkins, GitHub/GitLab, Bitbucket, and automated deployment pipelines.
• Strong critical thinking and analytical skills, with the ability to diagnose, troubleshoot, and solve complex technical problems effectively.

Nice to have

• AWS and Databricks certifications.
• Experience working with Azure and/or Google Cloud Platform (GCP).
• Exposure to Generative AI technologies including LLMs, RAG architectures, and Agentic AI systems, with experience designing and deploying AI-driven solutions.