Software Development Engineer - Data Platforms

Job Summary: As a seasoned Staff Software Development Engineer in Data Platform team you will be at the forefront of designing, building, and optimizing the critical data infrastructure that handles hundreds of millions of requests per minute (RPM) for our ingestion services, processes billions of events daily from Kafka, and manages petabytes of data stored in S3. You will leverage your deep expertise to architect and deliver highly scalable, reliable, and performant data solutions that directly impact our global user base and drive our strategic initiatives.

About the team:

Data platforms team at Jio Hot Star  is building the next generation of AI-powered experiences and autonomous agents, leveraging our vast data to create truly innovative products. Beyond traditional data engineering, you ll be instrumental in developing the data foundations for our AI initiatives, including the development of our own MCP server and the infrastructure supporting our cutting-edge AI Agents.

• Core Platform Development
• Architecture & Design:
  Build POCs, create architecture designs, and evaluate trade-offs for new services and migrations
• Real-time Data Pipeline:
  Build and maintain highly scalable, accurate, clean and real-time events collection systems
• Data Foundation for AI & MCP:
  Specifically design and build data pipelines to support the development and training of AI models and autonomous AI Agents.
• This includes creating robust data infrastructure for our MCP, ensuring data quality and availability for personalized learning paths and skill validation.
• Data Quality Assurance:
  Continuously work towards detecting, alerting, and fixing quality issues to build trust in our data
• System Enhancement:
  Improve existing systems and services using latest tooling and engineering standards
• Cost Optimization:
  Improve unit economics across ingestion, storage, and processing components

• Technical Leadership & Ownership
• Complete Development Lifecycle:
  Own the entire development process from ideation to deployment
• Cross-functional Collaboration:
  
  Work closely with different teams to achieve common goals through efficient coordination
• Technical Documentation:
  Maintain up-to-date documentation with architecture diagrams for entire projects
• Service Ownership:
  Take complete ownership of services within your workstream and drive continuous improvement
• Operational Excellence:
  Establish and maintain robust monitoring, alerting, and operational procedures for mission-critical data systems.

• Team Leadership & Growth
• Knowledge Sharing:
  Write blogs and articles to help team members and the community
• Architecture Breakdown:
  Break down high-level architecture into manageable services and tasks
• Technology Trends:
  Learn and share new trends in technology, engineering, and productivity
• Team Productivity:
  Actively work towards improving team productivity and knowledge
• Mentorship:
  Guide and mentor junior team members

• Business Impact
• Data Governance:
  Govern data assets across the entire company and audit data posture
• Time to Insight:
  Reduce time to insight for data team stakeholders
• Business Decision Support:
  Assist and challenge business decisions using data insights
• Stakeholder Service:
  Make data available to all stakeholders in an efficient, quick, quarriable, and intuitive manner

Skills and attributes for success:

• Experience:
  
  8+ years of progressive professional experience in data engineering, with a proven track record of designing, building, and operating large-scale, high-throughput data platforms, ideally in a consumer-facing or streaming industry.
• Extreme Scale
  
  Experience:
  
  Demonstrated experience working with data systems that handle hundreds of millions of events/requests per minute, billions of daily events, and petabytes of storage (e.g., S3, HDFS).
• Programming:
  Strong proficiency in at least one major programming language such as Python, Java, Scala, or Go, with a focus on building robust, production-grade data applications.
• Distributed Data Processing:
  Deep expertise and practical experience with distributed data processing frameworks like Apache Spark, Apache Flink, or equivalent technologies for batch and streaming workloads.
• AI/ML Data
  
  Experi…