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Tier-1 brand, popular Data Engineer title, and broad cloud/lakehouse skillset increase competitive density.
Specialized lakehouse, federation, and cloud control-plane expertise makes fit somewhat industry-specific but still transferable.
Explicit 10+ years requirement and extensive mandatory cloud, lakehouse, and platform technical skills enforce strict filtering.
Design and build scalable, secure, cloud-native and hybrid data platforms and control-plane services supporting batch, streaming, API, and secure data-sharing use cases.
Architect large-scale distributed and lakehouse platforms across multiple regions and clouds, establishing federated governance, metadata, access, and query patterns.
Own infrastructure optimization and establish platforms' architecture standards, mentoring engineers and collaborating cross-functionally to influence technical direction.
10+ years of hands-on data and software engineering experience with strong Java and/or Python, PySpark, API/backend service development skills.
Experience designing large-scale distributed or lakehouse platforms across multiple regions, clouds, or execution environments.
Strong cloud data-platform experience on AWS and/or Azure including key services like S3, IAM, Databricks, EKS, ADLS, AKS etc.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent hands-on experience.
Experienced architect and builder capable of defining control-plane and data-plane boundaries, governance, and federated metadata/query architectures.
Strong expertise in modern data architectures including lakehouse, medallion, batch/streaming processing, and secure data sharing.
Comfortable in hands-on coding, platform design, systems integration, and leading engineering standards and mentorship in a complex multi-cloud environment.