M
HyderabadTechnical Program ManagementTop payGCC
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Working through ambiguity, developing hypotheses and solutions, and coordinating across engineering and data teams to land defined problems end-to-end — with a bias toward repeatable, AI- and automation-assisted workflows — rounds out the profile. - Drive end-to-end quality for Fabric scenarios, covering both performance (latency, regressions) and reliability (success rates, failures, and timeouts). - Partner with engineering and data teams to onboard scenarios with complete, accurate telemetry, clear ownership, and measurable targets — and to refine the data pipelines, reporting models, and sampling strategies that keep signals consistent and accurate across environments. - Identify monitoring gaps across key customer journeys, improving signal quality and ensuring issues are detected early with minimal noise. - Support LiveSite by helping define alerting thresholds and partner with teams during incidents to investigate performance regressions and reliability issues, identify root causes, and drive follow-up actions. - Maintain and evolve the dashboards and reporting used in regular reviews — connecting performance and reliability signals into actionable insight tied to team commitments and end-to-end customer impact. - Drive cross-team coordination to unblock dependencies and align priorities, and create simple, repeatable documentation and onboarding paths so teams can adopt monitoring and alerting with minimal friction. - Bachelor's Degree AND 2+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience. - 1+ year(s) of experience managing cross-functional and/or cross-team projects. - Experience in performance monitoring, reliability, or observability systems - Experience with data analysis tools such as Kusto, SQL, or Power BI - Experience working with distributed systems or cloud platforms - Effective communication skills, with the ability to work across disciplines including engineering, product, and data engineering teams