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Strong employer brand and Bengaluru metro location with mid-level DataOps role produce moderate candidate competition.
Specialized DataOps and platform reliability skills transfer across industries but favor enterprise-scale data environments.
Explicit 6+ years requirement plus mandatory DataOps, cloud, observability, and platform leadership skills indicate high shortlisting strictness.
Own the DataOps strategy and operational roadmap ensuring pipeline reliability, incident management, and continuous delivery across enterprise data platforms.
Lead and manage a team of data engineers through the full Build + Run + Support lifecycle, including enforcing standards, conducting code reviews, and driving operational excellence.
Collaborate with stakeholders to mitigate operational risks, improve data quality operations, and drive adoption of CI/CD and observability practices.
Bachelor's degree in Computer Science, IT, Engineering, or related field; Master's preferred.
6+ years in data engineering with strong emphasis on data operations, platform reliability, and DataOps/DevOps practices.
Proven experience leading data engineering teams and managing delivery in fast-paced, cross-functional environments.
Strong technical skills including Python, SQL, automated testing frameworks (Great Expectations, dbt, pytest), CI/CD tools (Azure DevOps, GitHub Actions), cloud platforms (Azure preferred), pipeline orchestration, and monitoring frameworks.
Experienced leader in operationalizing enterprise-level data platforms with a focus on reducing pipeline failures and improving MTTR through systemic improvements.
Strong background in implementing DataOps and DevOps practices, data quality operations, and managing complex Agile/Kanban operational workflows.
Comfortable working cross-functionally with platform, cloud infrastructure, and security teams, and translating operational metrics into business impact.