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Mid-level Bengaluru role with specific platform and cloud skills yields moderate competition.
Platform engineering skills transfer across industries, though lakehouse and Databricks experience adds domain specificity.
Explicit 6–10 years plus mandatory Scala/Java/Python, Azure and production platform responsibilities increases filtering.
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Own and govern the data ingestion and integration architecture for an enterprise data platform, including batch, streaming, API, and event-driven frameworks.
Provide technical leadership and design authority ensuring scalability, reliability, and engineering quality across ingestion components and reusable platform patterns.
Lead and support globally distributed engineering teams, enforce software engineering standards, and collaborate with cross-functional stakeholders to maintain secure, compliant, and sustainable system design.
Degree in Computer Science or related field.
6–10 years of experience in software engineering and data platform development focused on large-scale enterprise systems.
Strong hands-on experience with Scala, Java, and Python in production environments.
Experience with data integration patterns (APIs, CDC, streaming, event-driven), CI/CD, automated testing, observability, and working in Microsoft Azure or similar hyperscaler environments.
Proven track record of technical leadership and architectural ownership in distributed data platforms or similar complex systems.
Ability to define and govern reusable frameworks, engineering standards, and scalable ingestion interfaces across multiple business domains.
Experience collaborating with global teams and guiding engineers in building production-grade, fault-tolerant ingestion services with a focus on advanced use cases like AI/ML integration.