Software Development Engineer II - Data Engineering

You'll also be contributing to the data foundations for our AI initiatives, including working on data pipelines that support our MCP server and infrastructure for cutting-edge AI Agents, while learning from experienced engineers and growing your expertise in large-scale data systems.

About the team: JioHotstar’s world-record-breaking OTT platform is available in India, the UK, Singapore, and Canada. We are home to India’s largest entertainment content catalog for the Indian diaspora in the UK. We are hiring senior engineers for our UK and international teams to develop systems that drive business growth in the country. This is a unique opportunity to work across the JioHotstar tech stack and work on the most impactful projects. You will contribute to the common stack, build frameworks to offer geography-specific differentiated features and create subscriber and business growth platform for the company. About Us

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

Key Responsibilities:

Feature Implementation: Develop and implement features for data ingestion, processing, governance, observability and storage systems based on technical specifications and guidance from senior engineers

Real-time Data Pipeline Contribution: Build components for highly scalable, accurate, and real-time event collection systems under the guidance of senior team members

Data Pipeline Development: Implement data pipelines to support AI model training and autonomous AI Agents, ensuring data quality and reliability

Code Quality: Write clean, maintainable, and well-tested code following established engineering standards and best practices

System Maintenance: Contribute to improving existing systems and services using modern tooling and engineering practices

Performance Optimization: Help identify and implement optimizations for ingestion, storage, and processing components

Skills and Attributes to success:

Data Processing: Hands-on experience with data processing frameworks like Apache Spark, Apache Flink, or similar technologies for batch and streaming workloads

AI/ML Pipeline Experience: Some exposure to building data pipelines for machine learning workflows, feature engineering, or model training (nice to have)

Messaging Systems: Experience with messaging queues and stream processing platforms like Apache Kafka, Kinesis, or equivalent

Cloud Platforms: Working knowledge of at least one major cloud platform (AWS, GCP, or Azure) and their data services, with preference for AWS (S3, EMR, Kinesis, etc.)

Data Storage: Understanding of modern data warehousing and data lake concepts (Snowflake, BigQuery, Redshift, Delta Lake)

ETL/Pipeline Tools: Experience building ETL/ELT pipelines using tools like Apache Airflow, Prefect, or similar orchestration systems

Databases: Solid SQL skills and experience with both relational (PostgreSQL, MySQL) and NoSQL databases (Cassandra, DynamoDB)

Monitoring: Experience with monitoring and observability tools (Datadog, Grafana, Prometheus etc.)

IaC : Familiarity with Infrastructure as Code (Terraform, CloudFormation)

Preferred Education & Experience:

Professional Experience: 2 - 4 years of software engineering experience with at least 2 years focused on data engineering or related fields

Scale Exposure: Experience working with large datasets and high-throughput systems (millions of events, terabytes of data)

Programming Skills: Proficiency in at least one major programming language such as Python, Java, Scala, or Go

System Design Understanding: Basic understanding of distributed systems concepts and data processing patterns