Lead Software Engineer - Data, Digital Business @ Sony Pictures Networks

Role involves leading SonyLIVs data engineering strategy, architecting scalable data infrastructure, driving innovation in data processing, ensuring operational excellence, and fostering a high-performance team to enable data-driven insights for OTT content and user engagement.

Responsibilities :

• Define the Technical Vision for Scalable Data Infrastructure: Establish a robust technical strategy for SonyLIV s data and analytics platform, architecting a scalable, high-performance data ecosystem using modern technologies like Spark, Kafka, Snowflake, and cloud services (AWS/GCP).

• Lead Innovation in Data Processing and Architecture: Advance SonyLIV s data engineering practices by implementing real-time data processing, optimized ETL pipelines, and streaming analytics through tools like Apache Airflow, Spark, and Kubernetes. Enable high-speed data processing to support real-time insights for content and user engagement.

• Ensure Operational Excellence in Data Systems: Set and enforce standards for data reliability, privacy, and performance. Define SLAs for production data processes, using monitoring tools (Grafana, Prometheus) to maintain system health and quickly resolve issues.

• Build and Mentor a High-Caliber Data Engineering Team: Recruit and lead a skilled team with strengths in distributed computing, cloud infrastructure, and data security. Foster a collaborative and innovative culture, focused on technical excellence and efficiency.

• Collaborate with Cross-Functional Teams: Partner closely with Data Scientists, Software Engineers, and Product Managers to deliver scalable data solutions for personalization algorithms, recommendation engines, and content analytics.

• Architect and Manage Production Data Models and Pipelines: Design and launch production-ready data models and pipelines capable of supporting millions of users. Utilize advanced storage and retrieval solutions like Hive, Presto, and BigQuery to ensure efficient data access.

• Drive Data Quality and Business Insights: Implement automated quality frameworks to maintain data accuracy and reliability. Oversee the creation of BI dashboards and data visualizations using tools like Tableau and Looker, providing actionable insights into user engagement and content performance.

This role offers the opportunity to lead SonyLIV s data engineering strategy, driving technological innovation and operational excellence while enabling data-driven decisions that shape the future of OTT entertainment.

Minimum Qualifications :

• 8+ years of progressive experience in data engineering, business intelligence, and data warehousing, including significant expertise in high-volume, real-time data environments.

• Proven track record in building, scaling, and managing large data engineering teams (10+ members), including experience managing managers and guiding teams through complex data challenges.

• Demonstrated success in designing and implementing scalable data architectures, with hands-on experience using modern data technologies (eg, Spark, Kafka, Redshift, Snowflake, BigQuery) for data ingestion, transformation, and storage.

• Advanced proficiency in SQL and experience with at least one object-oriented programming language (Python, Java, or similar) for custom data solutions and pipeline optimization.

• Strong experience in establishing and enforcing SLAs for data availability, accuracy, and latency, with a focus on data reliability and operational excellence.

• Extensive knowledge of A/B testing methodologies and statistical analysis, including a solid understanding of the application of these techniques for user engagement and content analytics in OTT environments.

• Skilled in data governance, data privacy, and compliance, with hands-on experience implementing security protocols and controls within large data ecosystems.

Preferred Qualifications:

• Bachelors or master s degree in computer science, Mathematics, Physics, or a related technical field.

• Experience managing the end-to-end data engineering lifecycle, from model design and data ingestion through to visualization and reporting.

• Experience working with large-scale infrastructure, including cloud data warehousing, distributed computing, and advanced storage solutions.

• Familiarity with automated data lineage and data auditing tools to streamline data governance and improve transparency.

• Expertise with BI and visualization tools (eg, Tableau, Looker) and advanced processing frameworks (eg, Hive, Presto) for managing high-volume data sets and delivering insights across the organization.