Staff Software Development Engineer Data Platforms

Bengaluru - India

Monthly Salary: Not Disclosed

Posted on: 22 hours ago

Vacancies: 1 Vacancy

Job Summary

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 JioHotStar 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 youll 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.

Key Responsibilities:

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 Experience: Specific experience in building data pipelines for Machine Learning model training inference and feature stores. Familiarity with data needs for AI Agents or similar intelligent systems.
Messaging & Streaming: Extensive experience with high-throughput messaging queues and stream processing platforms like Apache Kafka Kinesis or equivalent.
Cloud Platforms: Hands-on expertise with at least one major cloud platform (AWS GCP or Azure) and their data-related services with a strong preference for AWS (S3 EMR Kinesis Glue Redshift etc.).
Data Warehousing/Lakes: Strong understanding and hands-on experience with modern data warehousing concepts and data lake architectures (e.g. Snowflake BigQuery Redshift Delta Lake Iceberg Hudi).
ETL/Orchestration: Expertise in building optimizing and orchestrating complex ETL/ELT pipelines using tools like Apache Airflow Prefect or other workflow management systems.
Databases: Strong SQL skills and experience with both relational (e.g. PostgreSQL MySQL) and NoSQL databases (e.g. Cassandra DynamoDB).
Data Modeling: Advanced data modeling skills (dimensional Kimball data vault) for large complex datasets.
Problem-Solving: Exceptional analytical and problem-solving abilities with a proven track record of debugging and optimizing complex distributed systems.
Communication: Excellent communication collaboration and interpersonal skills with the ability to articulate complex technical concepts to diverse audiences.
Mentorship: Proven ability to mentor guide and technically lead senior and junior engineers.

Perched firmly at the nucleus of spellbinding content and innovative technology JioStar is a leading global media & entertainment company that is reimagining the way audiences consume entertainment and sports. Its television network and streaming service together reach more than 750 million viewers every week igniting the dreams and aspirations of hundreds of million people across geographies.

JioStar is an equal opportunity employer. The company values diversity and its mission is to create a workplace where everyone can bring their authentic selves to work. The company ensures that the work environment is free from any discrimination against persons with disabilities gender gender identity and any other characteristics or status that is legally protected.

If you would like more information about how your data is processed please contact us.

Required Experience:

Staff IC

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 even...

About the team:

Key Responsibilities:

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 Experience: Specific experience in building data pipelines for Machine Learning model training inference and feature stores. Familiarity with data needs for AI Agents or similar intelligent systems.
Messaging & Streaming: Extensive experience with high-throughput messaging queues and stream processing platforms like Apache Kafka Kinesis or equivalent.
Cloud Platforms: Hands-on expertise with at least one major cloud platform (AWS GCP or Azure) and their data-related services with a strong preference for AWS (S3 EMR Kinesis Glue Redshift etc.).
Data Warehousing/Lakes: Strong understanding and hands-on experience with modern data warehousing concepts and data lake architectures (e.g. Snowflake BigQuery Redshift Delta Lake Iceberg Hudi).
ETL/Orchestration: Expertise in building optimizing and orchestrating complex ETL/ELT pipelines using tools like Apache Airflow Prefect or other workflow management systems.
Databases: Strong SQL skills and experience with both relational (e.g. PostgreSQL MySQL) and NoSQL databases (e.g. Cassandra DynamoDB).
Data Modeling: Advanced data modeling skills (dimensional Kimball data vault) for large complex datasets.
Problem-Solving: Exceptional analytical and problem-solving abilities with a proven track record of debugging and optimizing complex distributed systems.
Communication: Excellent communication collaboration and interpersonal skills with the ability to articulate complex technical concepts to diverse audiences.
Mentorship: Proven ability to mentor guide and technically lead senior and junior engineers.

If you would like more information about how your data is processed please contact us.

Required Experience:

Staff IC

Key Skills

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About Company

JioStar

JioStar combines the power of Reliance’s Viacom18 and Disney Star, delivering unmatched entertainment with 120+ TV channels and two leading streaming platforms. Explore a new era of content with JioStar.

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