Software Development Engineer - Data Engineer

Job Summary:

The Data Engineer will be responsible for designing, building, and maintaining scalable and reliable data pipelines and data platforms to support analytics, reporting, and downstream applications. The role involves working across the entire data lifecycle - ingestion, processing, storage, and consumption with a strong focus on data quality, performance, and operational stability.

The engineer will work closely with analytics teams, business stakeholders, and platform teams to enable timely and accurate data availability across multiple use cases.

About the team:

Join JioStar's business systems team, where you'll build scalable platforms that empower data-driven campaign decisions across TV and Digital channels. You'll work on systems that help business users optimise advertiser coverage, maximise viewership reach through TVR/Digital impressions, and analyse how users adopt micro-content across demographic and geographic cohorts. We're solving complex problems at massive scale-enabling clarity on user adoption patterns by gender, economic class, and geography-so our business teams can make informed decisions on content strategy and revenue optimisation. If you're passionate about building high-performance systems that drive business impact at billion-user scale, join us

Key responsibilities:

• Design, develop, and maintain batch and near real-time data pipelines using modern data engineering frameworks and tools
• Implement and manage data ingestion, ETL/ELT workflows, and data transformations from multiple internal and external data sources
• Build and optimize scalable data processing solutions using distributed computing frameworks (e.g., Spark)
• Develop and manage datasets for analytics, dashboards, and reporting use cases
• Monitor pipeline performance, data freshness, and reliability; proactively identify and resolve issues
• Work with stakeholders to understand data requirements and translate them into technical solutions
• Ensure adherence to data governance, security, and best engineering practices
• Participate in code reviews, design discussions, and continuous improvement initiatives

Skills and attributes for success:

• Strong experience with data engineering and data pipelining concepts
• Hands-on experience with distributed data processing frameworks such as Apache Spark
• Experience building data solutions on Google Cloud Platform (GCP), including components such as Google Cloud Storage (GCS), BigQuery, Dataproc / Dataflow, Pub/Sub
• Strong SQL skills and experience working with large datasets
• Proficiency in Python (Java/Scala is a plus)
• Experience integrating data from multiple heterogeneous data sources
• Solid understanding of distributed systems, parallel processing, and performance optimization

Preferred education and experience:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent practical experience)
• 5-7 years of hands-on experience in data engineering/ big data roles
• Strong experience working in complex, large-scale data environments