Data Engineer AI/ML Data Platforms & Real-Time Pipelines

As a Data Engineer at Jio Reality Labs located in Navi Mumbai, India, you will be responsible for designing, building, and maintaining scalable data platforms that power AI/ML and reinforcement learning systems, catering to millions of users. Your role will involve creating robust data ingestion, processing, and analytics pipelines to enable real-time model training, inference, and continuous learning. If you are passionate about constructing high-performance data systems for next-generation AI products, we are excited to hear from you. Key Responsibilities: - Data Pipeline Development & Architecture: - Design end-to-end batch and real-time data pipelines for AI/ML model training, inference, and analytics at scale. - Build reliable ingestion frameworks for structured and unstructured data from various sources like user interactions, sensors, and application logs. - Real-Time & Streaming Data Systems: - Develop low-latency streaming pipelines using technologies such as Kafka, Kinesis, or Pub/Sub to support real-time decision-making and reinforcement learning feedback loops. - Ensure data quality, consistency, and fault tolerance across streaming systems. - Data Modeling & Storage: - Design efficient data models and schemas optimized for analytics, ML training, and reporting. - Manage and optimize data storage across relational, NoSQL, and analytical data stores for scalability and cost efficiency. - Cloud Data Infrastructure: - Build and operate cloud-native data platforms on AWS, GCP, or Azure. - Implement scalable compute and storage solutions to handle large volumes of data with high throughput and reliability. - MLOps & Analytics Enablement: - Collaborate with data scientists and ML engineers to facilitate seamless data access for model training, feature engineering, and experimentation. - Support feature stores, data versioning, and reproducible pipelines for ML workflows. - Data Quality, Security & Governance: - Implement data validation, monitoring, and lineage frameworks to ensure high data quality and trust. - Apply best practices in data security, encryption, access controls, and compliance to safeguard sensitive user and business data. Qualifications Required: - Strong experience in data engineering using Python and SQL. - Hands-on experience in building batch and real-time data pipelines. - Proficiency with streaming platforms like Kafka, Kinesis, or Pub/Sub. - Experience in designing and managing data warehouses and data lakes (BigQuery, Redshift, Snowflake, S3, ADLS). - Strong understanding of data modeling, schema design, and performance optimization. - Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud. - Experience with CI/CD pipelines for data workflows and production deployments. - Knowledge of data security, access control, and compliance best practices. Additional Details: Jio Reality Labs offers you the opportunity to work on data platforms for next-generation AI, AR/VR, and immersive technologies. You will contribute to petabyte-scale data systems supporting millions of users in a collaborative, fast-paced environment with a strong ownership and learning culture. Additionally, we provide competitive compensation, benefits, and long-term growth opportunities. Preferred Skills: - Experience with distributed data processing frameworks such as Apache Spark, Flink, or Beam. - Familiarity with feature stores and ML data lifecycle management. - Exposure to reinforcement learning data pipelines and real-time feedback systems. - Knowledge of edge data processing for latency-sensitive AI applications. - Experience working in high-scale consumer or AI-driven products. As a Data Engineer at Jio Reality Labs located in Navi Mumbai, India, you will be responsible for designing, building, and maintaining scalable data platforms that power AI/ML and reinforcement learning systems, catering to millions of users. Your role will involve creating robust data ingestion, processing, and analytics pipelines to enable real-time model training, inference, and continuous learning. If you are passionate about constructing high-performance data systems for next-generation AI products, we are excited to hear from you. Key Responsibilities: - Data Pipeline Development & Architecture: - Design end-to-end batch and real-time data pipelines for AI/ML model training, inference, and analytics at scale. - Build reliable ingestion frameworks for structured and unstructured data from various sources like user interactions, sensors, and application logs. - Real-Time & Streaming Data Systems: - Develop low-latency streaming pipelines using technologies such as Kafka, Kinesis, or Pub/Sub to support real-time decision-making and reinforcement learning feedback loops. - Ensure data quality, consistency, and fault tolerance across streaming systems. - Data Modeling & Storage: - Design efficient data mod