Location: Navi Mumbai, India
Job Type: Full-Time
Job Summary
Jio Reality Labs is seeking an experienced Data Engineer to design, build, and maintain scalable data
platforms that power our AI/ML and reinforcement learning systems, serving millions of users. This
role will focus on creating robust data ingestion, processing, and analytics pipelines that enable realtime model training, inference, and continuous learning. If you are passionate about building highperformance data systems for next-generation AI products, we'd love to hear from you.
Responsibilities
- Data Pipeline Development & Architecture
Design and implement end-to-end batch and real-time data pipelines to support AI/ML
model training, inference, and analytics at scale. Build reliable ingestion frameworks for
structured and unstructured data from multiple sources including 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 decisioning and reinforcement learning feedback loops. Ensure
data quality, consistency, and fault tolerance across streaming systems.
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 to ensure 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
Partner with data scientists and ML engineers to enable 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 protect sensitive user and business data.
Required Skills And Qualifications
Strong experience in data engineering using Python and SQL.
Hands-on experience building batch and real-time data pipelines.
Proficiency with streaming platforms such as Kafka, Kinesis, or Pub/Sub.
Experience 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.
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.
What We Offer
Opportunity to build data platforms for next-generation AI, AR/VR, and immersive
technologies.
Work on petabyte-scale data systems supporting millions of users.
Collaborative, fast-paced environment with strong ownership and learning culture.
Competitive Compensation, Benefits, And Long-term Growth Opportunities.
Skills: ml,pipelines,python,kafka,bigquery,kinesis,adls,nosql,platforms,data,analytics,sql,learning,design,snowflake,ai/ml,redshift,cloud
