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Senior, highly specialized big-data role at a mid-tier company yields moderate competition.
Requires deep big-data and streaming expertise, but skills transfer across industries with similar scale.
Multiple explicit mandatory years and specialized big-data tech requirements create strict shortlisting filters.
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Define and lead the technical vision and long-term strategy for a high-scale data platform and pipeline architecture handling billions of daily events and transactions.
Design, optimize, and maintain scalable, highly available distributed data systems focused on performance, reliability, and cost-efficiency.
Lead architectural decisions across multiple engineering teams, troubleshoot performance bottlenecks, mentor engineers, and set platform engineering standards.
Minimum 12 years of experience in software, data, or distributed systems engineering.
At least 6 years hands-on with Apache Spark and building large-scale data pipelines processing billions of events daily.
Minimum 4 years experience administering and operating Apache Kafka in production.
Bachelor's degree in Computer Science, Software Engineering, Information Technology, or related technical discipline.
Proven leader capable of driving architecture strategy and technical initiatives across multiple engineering teams.
Deep expertise in designing, operating, and troubleshooting large-scale distributed data processing systems and streaming architectures.
Experienced mentor focused on engineering excellence and ability to manage complex, high-availability big data platforms integrating multiple open-source technologies.