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Tier-1 brand, metro location, and broad platform requirements create moderate competition.
Core data platform skills transfer across industries, but payments governance and federation increase domain specificity.
Explicit 10+ years, principal-level data platform expertise, and many mandatory technologies raise shortlisting strictness.
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 data and lakehouse platforms across multiple regions, public clouds, and on-premises environments with governance and metadata frameworks.
Own infrastructure optimization, define standards for data product contracts and federated metadata, and mentor engineers while influencing technical direction and engineering culture.
10+ years of hands-on data and software engineering experience with strong Java and/or Python, PySpark, API and backend service development skills.
Proven experience designing large-scale distributed or lakehouse platforms across multiple regions, clouds, clusters, or execution environments.
Strong cloud data-platform experience with AWS, Azure, or GCP services (e.g., AWS S3, IAM, Glue; Azure ADLS, Entra ID, RBAC, Data Factory).
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent hands-on experience.
Experienced architect in control-plane and data-plane distributed systems with strong understanding of global governance and local enforcement boundaries.
Proficient in modern data architecture technologies including Databricks, Snowflake, Spark, Kubernetes, Delta Lake, Iceberg, Unity Catalog, AWS Glue Data Catalog, and federated metadata/query patterns.
Skilled in defining architecture decisions, reusable components, engineering standards, and fostering collaboration in Agile environments.