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Senior role but popular Data Engineer skills and likely metro location yield moderate candidate competition.
Role requires deep enterprise Snowflake/Azure data engineering and domain-specific pipelines, limiting cross-industry transferability.
Explicit 12-16 years plus many mandatory Snowflake/Azure and data engineering skills makes screening highly strict.
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Own end-to-end delivery and lifecycle management of enterprise-scale, governed data products and AI capabilities within Market-to-Order Commercial Operations.
Design, deploy, and optimize scalable Snowflake and Azure data engineering solutions ensuring performance, security, and cost efficiency.
Lead technical design and code reviews, mentor engineers, and partner with cross-functional stakeholders to drive continuous improvement and rapid business value.
12-16 years of experience in data engineering, data warehousing, ELT/ETL development, and cloud data platforms with enterprise production pipeline delivery.
Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related discipline from accredited institution.
Proven expertise in Snowflake and Azure data services including Azure Data Factory and Azure Data Lake Storage.
Strong programming skills in Python, Scala, SQL, PL-SQL, and advanced proficiency in SQL performance tuning and query optimization.
Senior individual contributor with deep technical ownership and leadership capabilities in complex data engineering and AI-augmented development environments.
Experienced in modern cloud-native data engineering with strong focus on specification-driven development, DevSecOps, DataOps, and automated deployment in Agile contexts.
Comfortable leading cross-functional collaboration globally, mentoring peers, and managing delivery risks across multiple initiatives without direct authority.