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Metro location and senior data role increase competition, but specialized Snowflake and streaming expertise moderate density.
Core data engineering skills transfer across industries, but Snowflake and enterprise governance requirements make fit moderately sensitive.
Explicit 9+ years plus mandatory Snowflake, AWS streaming, SnapLogic, observability, and governance skills imply high strictness.
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Lead design and evolution of scalable, secure, and high-performance cloud-native data platforms using Snowflake and AWS technologies.
Define enterprise data architecture and oversee the design, optimization, and reliability of batch and real-time data pipelines, including production troubleshooting and cost optimization.
Mentor engineering teams, drive architectural best practices, and collaborate across product, analytics, DevOps, and business units for end-to-end data platform delivery.
9+ years experience in Data Engineering, Data Warehousing, or Data Platform development.
7+ years experience designing enterprise-scale data architectures.
Deep expertise in Snowflake (Snowpipe, COPY INTO, Streams, Tasks, Dynamic Tables, Stored Procedures) and AWS services (S3, Kinesis, Lambda).
Job location: Noida. Work Experience Required: 9+ years (explicit). Notice period: Not explicitly mentioned in the JD.
Experienced in cloud-native, scalable data architectures with strong hands-on skills in Snowflake and AWS streaming/event-driven pipelines.
Proven ability in production support, incident management, performance tuning, and data governance implementation in enterprise settings.
Skilled in mentoring engineers, creating architecture documentation (HLD, LLD, UML), and driving best practices in Agile environments.