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Metro Bangalore, broad AWS/data skillset, and mid-level attractiveness create high applicant competition.
Data architecture skills are broadly transferable across industries with common cloud and data toolchains.
Explicit 6+ years requirement and mandatory AWS data stack increase shortlisting rigor.
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Design and implement scalable, secure, and high-performance data architectures on AWS aligned with business requirements.
Lead data engineering projects from requirements gathering through deployment, including developing data models, ETL processes, and integration solutions.
Collaborate with sales and technical teams for customer workshops, solution scoping, and delivering technical presentations and POCs.
6+ years overall experience including design, deployment, and transformation roles.
4+ years of experience working with complex AWS cloud environments.
At least 5 years of experience in data engineering or data architecture with proven expertise in AWS services like Redshift, Glue, S3, Lambda, RDS, and EMR.
Proficiency in SQL, Python, and experience with data modeling, ETL, big data technologies (Hadoop, Spark, Kafka).
Experienced in leading technically complex AWS data architecture and engineering solutions in customer-facing consulting or project delivery roles.
Strong cross-functional collaboration skills working with sales, technical teams, and customers on solution design, scoping, and presentations.
Deep technical expertise in AWS data services and big data technologies with a track record of deploying enterprise-scale data solutions.