Lead Software Engineer

As a Lead Software Engineer in the CDP team, you will drive design, delivery, technical strategy, and execution for critically important data systems. You will define engineering standards, influence long-term platform direction, mentor junior engineers, and ensure the CDP and Foundations platform scales securely and reliably to support sustained business growth.

• Deliver large-scale cloud-native data platforms primarily on AWS employing REST APIs, micro services and event driven applications to build highly scalable and resilient systems.
• Work hands-on across the technology stack - including Java, Python, Spark, TypeScript, JavaScript, Angular, AWS services, event-driven architectures, and SQL/NoSQL databases - to solve complex engineering challenges and maintain platform excellence.
• Lead product wide technical initiatives focused on performance optimization, scalability, reliability, security, governance, and cost efficiency.
• Partner closely with global engineering, product management, architecture, and business stakeholders 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.
• 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.
• 8-10 years of strong software engineering experience, with deep expertise in building scalable UX driven applications and distributed systems architecture.
• Proven experience designing and building scalable REST APIs, microservices, Kubernetes, and distributed systems.
• Experience in Data Warehousing, Data Lakes, Delta Lake architecture, and modern big data ecosystem designs.
• Strong hands-on expertise in Python, Java, Angular and well-versed with Object oriented design patterns and Functional programming.
• Expertise in PySpark, and Apache Spark, with proven experience building high-performance distributed data processing solutions.
• Solid depth in Micro-services development with Kubernetes containerization for eventing and serving.
• Extensive experience with AWS services such as S3, Lambda, API Gateway, and EventBridge for building scalable, reliable, cloud-native data platforms.
• Strong experience with messaging and event-driven technologies such as Kafka, SNS, and SQS, along with solid expertise in relational and NoSQL databases including PostgreSQL, SQL Server, Aurora, DynamoDB, MongoDB, and Redis.
• Hands-on experience with Infrastructure as Code (IaC) tools such as Terraform and Ansible.
• Strong understanding of CI/CD and DevOps practices using tools such as Jenkins, GitHub/GitLab, Bitbucket, GoCD, and automated deployment pipelines.
• Experience implementing robust testing strategies, including unit, integration, and regression testing, while adhering to engineering best practices.
• Strong critical thinking and analytical skills, with the ability to diagnose, troubleshoot, and solve complex technical problems effectively.
• Exposure to Generative AI technologies, including LLMs, RAG architectures, and Agentic AI systems.

Nice to have:

• Working knowledge of PySpark with Databricks.
• Experience working with Azure and/or Google Cloud Platform (GCP).
• Experience building data platforms in privacy-safe or Customer Data Platforms and Marketing Technology environments.