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Senior, specialized Data/AI Ops role reduces applicant pool despite Bengaluru metro demand.
Strong Snowflake, DataOps, and MLOps focus limits industry portability.
Explicit 8–12 years plus deep Snowflake, DataOps, MLOps, and automation requirements enforce strict shortlisting.
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Own end-to-end Data & AI Operations and production support for enterprise data platforms, including Snowflake, data pipelines, AI/ML workloads ensuring SLAs, reliability, and performance.
Establish and improve operating models, automation, observability, governance, and controls to run Data & AI platforms as secure, cost-efficient enterprise services.
Design, build, and deploy engineering solutions and automation using Python, RPA, APIs, and AI/GenAI tools for operational excellence and incident management.
8–12 years of experience in Data Engineering, Data Platforms, Data Ops, Cloud Engineering or Production Operations with leadership exposure.
Deep hands-on expertise in Snowflake architecture, administration, SQL, performance tuning, workload management, security/RBAC, and cost optimization.
Experience with automation using RPA, Python, APIs, workflow automation, and AI/GenAI tools.
Location requirement: Prefer candidates residing in Bangalore; 3 days WFO; shift timing 12 noon to 9 pm; weekend on-call support required.
Technical leader capable of hands-on engineering and managing end-to-end Data & AI operational lifecycle with measurable business outcomes.
Strong domain expertise in Snowflake, DataOps, MLOps, and enterprise production operations including incident/problem/change management.
Proven experience in building and operationalizing automation, observability, FinOps and governance controls at scale in a complex enterprise Data & AI environment.