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Tier-1 brand and metro location counterbalanced by senior, niche principal-level requirement.
Deep enterprise data engineering and GenAI production experience yields low transferability outside data/finance domains.
Explicit 12+ years and mandatory hands-on data/AI/platform experience make filters highly stringent.
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Design, build, deploy, and operate large-scale, enterprise data platforms and scalable ETL/ELT pipelines specializing in AI/ML and GenAI workloads.
Use AI/ML and GenAI techniques to innovate the design, automation, optimization, validation, and documentation of data pipelines and workflows.
Provide architectural ownership and senior technical leadership including mentoring, architectural reviews, and setting engineering standards in cross-functional Agile environments.
12+ years experience owning and operating large-scale data engineering platforms in production.
Strong hands-on expertise in Python and SQL and experience with cloud data platforms (AWS, Azure, or GCP).
Proven experience architecting distributed, high-performance data systems incorporating AI/ML or GenAI for pipeline design and optimization.
Work Experience Required: 12+ years
Experienced senior engineer with a strong background in AI/ML-powered data engineering and platform modernization at enterprise scale.
Capable of hands-on leadership combining architecture ownership and mentoring (player-coach model).
Comfortable working in fast-paced, cross-functional, Agile teams delivering regulated, production-grade data and AI platforms.