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Tier-1 brand, metro location, and common data-engineering leadership title increase candidate competition.
Data engineering skills transfer across industries, but governance and regulated-data experience increases domain specificity.
Explicit 10+ years and mandatory data platform, cloud, and governance skills make shortlisting highly selective.
Lead design and delivery of scalable batch and streaming data platforms supporting analytics, reporting, and AI use cases.
Manage and mentor multidisciplinary teams (Data Engineering, Platform Engineering, DevOps) while establishing engineering standards, reusable frameworks, and delivery roadmaps.
Drive cloud platform modernization on AWS focusing on reliable data pipelines with strong governance, observability, security, and compliance for trusted data products.
10+ years in Data Engineering, Software Engineering, or Platform Engineering with leadership experience.
Proven experience with large-scale batch and streaming data platforms using Apache Spark, Kafka, Kinesis, Flink or equivalents.
Strong expertise in AWS cloud services covering data, compute, orchestration, and infrastructure.
Experience with modern data lake, warehouse, or lakehouse technologies such as Snowflake, Databricks, Redshift, Athena, Iceberg, or Delta Lake.
Experienced engineering leader capable of managing and scaling multidisciplinary teams in a cloud environment.
Deep technical background in operating and modernizing data platforms with a strong focus on AWS and real-time data pipelines.
Capable of collaborating cross-functionally with Product, Architecture, Governance, and Business stakeholders to align technical delivery with business goals.