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Tier-1 brand and metro location increase competition, but senior specialized data-platform focus narrows applicant pool.
Core data-platform and production ML skills transferable, though streaming/media experience is advantageous.
Explicit 10+ years plus strict large-scale data platform, cloud, and production ML requirements.
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Architect and build scalable, reliable large-scale data platform systems including pipelines, data lakes, and serving infrastructure processing billions of events.
Develop foundational infrastructure enabling AI and ML capabilities such as feature platforms, training data pipelines, and model-serving infrastructure.
Drive technical standards, mentor engineers, and influence organization-wide engineering strategy related to data engineering and applied AI.
10+ years of software engineering experience building and maintaining scalable software systems.
Extensive experience designing and deploying production-grade large-scale data platforms.
Proficiency in programming languages like Python, Scala, or Java and deep knowledge of distributed data processing frameworks such as Spark, Flink, Kafka.
Hands-on experience with cloud data infrastructure (AWS/GCP) and practical experience enabling ML/AI in production including feature pipelines and model serving.
Proven technical leadership in setting direction and driving cross-team initiatives in large-scale data and AI platform environments.
Experience bridging data engineering with applied AI/ML to productionize models and AI-powered capabilities.
Background in building data platforms supporting high-volume streaming or consumer platforms, preferably within media or entertainment sectors.