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Senior, niche lakehouse/AWS expertise reduces applicant density despite metro location.
Role requires deep, specialized data platform and Lakehouse expertise, limiting cross-domain transferability.
Mandatory 8+ years and extensive, specific technical stack requirements create strict filtering.
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Lead design, architecture, and implementation of enterprise-scale AWS data platforms and Lakehouse solutions.
Provide technical leadership throughout project lifecycle including architecture, technology selection, deployment, and production support.
Mentor globally distributed engineering teams and collaborate with stakeholders to deliver scalable, secure, and high-performance data solutions.
7-12 years of experience in designing and delivering enterprise-scale Data Lake, Lakehouse, or Data Warehouse solutions on AWS.
Strong hands-on expertise with SQL (analytical queries, window functions, stored procedures), Spark/PySpark, Python, and Apache Iceberg.
Experience with AWS services including EMR, S3, Athena, Glue Catalog, Aurora PostgreSQL, Lambda, CloudWatch, SQS, SNS, EventBridge, IAM.
Work Experience Required: 7+ years in relevant domain. Location: Mumbai/Bangalore.
Proven ability to lead end-to-end cloud-native data platform implementations with focus on architecture and operational support.
Strong architectural judgement with skills in defining cloud data platform architectures, technology evaluation, and informing best practices.
Experience mentoring teams, conducting architecture/code reviews, and collaborating across business and technical stakeholders for scalable solutions.