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Senior, niche data-platform leadership with limited mid-level appeal reduces applicant density.
Automotive/IoT preference increases domain sensitivity though core data-engineering skills remain transferable.
Explicit 15-22 years plus mandatory data platform and leadership experience creates strict screening filters.
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Define and implement a scalable, unified real-time automotive data platform architecture.
Oversee end-to-end integration and ensure high data quality, security, and governance.
Lead and develop a data engineering team while standardizing tools and practices.
15-22 years total experience with minimum 10 years in data engineering, including 5 years in leadership roles managing large-scale platforms.
Degree: BE/ME in Electrical and Electronics.
Strong expertise in data platform architecture, data lakes/warehouses, ETL/ELT, and real-time data processing.
Proficiency with big data tools (e.g., Spark, Kafka), cloud platforms (AWS/Azure/GCP), containerization, automation, and version control.
Experienced leader in data engineering managing scalable, real-time data platforms in automotive, IoT, or technology-driven industries.
Technically adept in big data ecosystem and cloud services with proven ability to build governed, secure data infrastructures.
Capable of collaborating cross-functionally and driving standards and innovation in large teams and complex environments.