Description

Responsibilities

• Deliver large-scale cloud-native data platforms primarily on AWS leveraging REST APIs, microservices, 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.
• Drive performance optimization, scalability, reliability, security, governance, and cost efficiency.
• Collaborate and develop 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.

Qualifications

• Required
  • 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 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, and Angular; well-versed with object-oriented design patterns and functional programming.
  • Experience in PySpark and Apache Spark, with proven experience building high-performance distributed data processing solutions.
  • Depth in microservices development with Kubernetes containerization for eventing and serving.
  • 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.
  • 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.
  • 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 and awareness of Generative AI technologies, including LLMs, RAG architectures, and Agentic AI systems.
• Preferred
  • 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

Key Skills

Education

Bachelor's degree