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Tier‑1 employer and Bangalore metro increase competition, but seniority and specialization reduce applicant pool.
Specialized distributed data platform, cloud-native, and regulated-finance experience limit cross-industry transferability.
Explicit 10+ years and principal-level multi-domain expertise create stringent technical filters.
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Architect and deliver core components of a distributed data platform supporting streaming, batch, and interactive workloads.
Set strategy and operating standards for AI-enabled engineering automation across a portfolio to drive improvements in delivery speed, reliability, and code quality with defined guardrails for validation and security.
Implement resilient distributed workflows, optimize compute and storage layers, embed security and compliance controls, define SLIs/SLOs, automate alerts, and mentor senior engineers.
10+ years of applied experience with formal training or certification in software engineering concepts.
Ownership experience with cloud-native distributed systems or data platforms at scale.
Deep expertise in at least two areas: cloud platforms, storage/lakehouse tech, data processing/streaming, query/compute engines, distributed systems, security/governance, or DevOps/SRE.
Proficient in coding with Java, Scala, Python, or Go; experience in large corporate environments with strong system design and communication skills.
Experienced in designing and scaling agentic AI-enabled development patterns with governance for validation, auditability, and secure handling of sensitive data.
Strong understanding of responsible AI use, security, resiliency, data sensitivity, and risk-based governance advising senior leaders.
Familiar with regulated or mission-critical environments, data governance stacks, data quality frameworks, policy engines, and possibly ML/AI data patterns.