Staff Engineer - Data, Digital Business (Data Engineer)

8 - 12 years

0 Lacs

Posted:14 hours ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

As a Staff Engineer - Data at SonyLIV's Digital Business, your role is crucial in leading the data engineering strategy and architecting scalable data infrastructure to drive innovation in data processing. You will be responsible for ensuring operational excellence, building a high-performance team, and enabling data-driven insights for OTT content and user engagement. Based in Mumbai, this position requires a minimum of 8 years of experience in the field. **Key Responsibilities:** - Define the technical vision for scalable data infrastructure using modern technologies like Spark, Kafka, Snowflake, and cloud services. - Lead innovation in data processing and architecture through real-time data processing and streaming analytics. - Ensure operational excellence in data systems by setting and enforcing standards for data reliability and privacy. - Build and mentor a high-caliber data engineering team. - Collaborate with cross-functional teams and drive data quality and business insights through automated quality frameworks and BI dashboards. **Qualifications Required:** - 8+ years of experience in data engineering, business intelligence, and data warehousing. - Expertise in high-volume, real-time data environments. - Proven track record in building and managing large data engineering teams. - Designing and implementing scalable data architectures. - Proficiency in SQL, experience with object-oriented programming languages. - Knowledge of A/B testing methodologies and statistical analysis. Joining SonyLIV provides you with the opportunity to drive the future of data-driven entertainment. You will collaborate with industry professionals, work with comprehensive data sets, leverage cutting-edge technology, and make a tangible impact on product delivery and user engagement. The ideal candidate will bring a strong foundation in data infrastructure, experience in leading and scaling data teams, and a focus on operational excellence to enhance efficiency.,

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