Engineering Manager, Data Engineering
Fox Corporation
- Location
- IND-KA-Bengaluru
- Work model
- On-Site
- Level
- Mid
- Posted
- 20h ago
Skills
About this role
OVERVIEW OF THE COMPANY Fox Corporation Under the FOX banner, we produce and distribute content through some of the world’s leading and most valued brands, including: FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations and Tubi Media Group. We empower a diverse range of creators to imagine and develop culturally significant content, while building an organization that thrives on creative ideas, operational expertise and strategic thinking.
JOB DESCRIPTION
Fox Corporation: Fox Corporation is home to industry-leading brands including FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations, and Tubi Media Group. We combine innovative technology, deep data insights, and world-class content to shape the future of digital entertainment. Our DTC platforms are built to deliver highly personalized, scalable user experiences to millions of global users.
ABOUT THE ROLE
FOX Corporation is looking for an experienced Engineering Manager, Data Engineering to lead our Data Engineering team responsible for building scalable, reliable, and high-performance data platforms that power business intelligence, analytics, machine learning, and operational reporting across FOX's Digital Product ecosystem. You will be responsible for building, mentoring, and scaling a high-performing engineering team while driving technical excellence and delivering robust data solutions. Our Data Engineering team is responsible for designing, developing, and maintaining modern cloud-based data platforms that ingest, process, transform, and deliver data from millions of customer interactions across our digital products. Leveraging cloud-native technologies, distributed computing frameworks, and modern data architectures, the team builds reliable and scalable data pipelines that enable real-time analytics and business insights. With a strong emphasis on data quality, governance, scalability, and operational excellence, the team ensures trusted data is available across the organization. As an Engineering Manager – Data Engineering , you will lead and grow a high-performing engineering team responsible for delivering scalable data platforms and pipelines. You will partner closely with Product, Analytics, Data Science, Platform Engineering, DevOps, and Architecture teams to drive data initiatives while fostering a culture of ownership, innovation, collaboration, and continuous improvement. A SNAPSHOT OF YOUR RESPONSIBILITIES Lead, mentor, and grow a team of Data Engineers through coaching, feedback, and career development. Foster a culture of ownership, collaboration, innovation, and continuous improvement within the engineering team. Drive the design, development, and optimization of scalable batch and real-time data pipelines. Partner with senior engineers to improve data architecture, platform scalability, reliability, security, and performance. Lead technical design reviews and provide guidance on modern data engineering best practices. Own the delivery of data engineering initiatives from planning through production deployment. Balance business priorities with long-term platform scalability, maintainability, and technical debt reduction. Collaborate closely with Product Managers, Data Scientists, Analytics teams, Platform Engineering, DevOps, and Architecture to define priorities and delivery roadmaps. Ensure engineering teams follow Agile development methodologies and continuous integration and deployment practices. Establish engineering standards for data quality, observability, monitoring, testing, governance, and documentation. Drive improvements in data platform performance, availability, reliability, and operational efficiency. Monitor project execution, proactively identify delivery risks, and remove technical and organizational blockers. Mentor engineers while supporting technical growth, career development, and succession planning. Communicate project status, technical trade-offs, delivery risks, and engineering metrics