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Tier-1 brand and Bangalore location increase competition; senior, niche Databricks requirement moderates density.
Core data engineering skills transferable, but product analytics and enterprise process context require domain familiarity.
Explicit 10+ years, Staff level, and Databricks/multi-cloud requirements make shortlisting highly strict.
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Design, build, and maintain scalable, resilient data infrastructure to support product analytics from diverse sources including enterprise systems, telemetry, and observability.
Lead implementation of Celonis Digital Twin data foundation enabling strategic and tactical decision-making in a hyper-growth SaaS environment.
Facilitate data-driven stakeholder discussions and provide analytic investigations to support business and product decisions through effective storytelling.
Bachelor's degree in Mathematics, Computer Science, or Data Science; Master’s or PhD preferred.
10+ years of relevant experience as Analytics Engineer/Data Engineer in SaaS or enterprise software environment.
Extensive experience building scalable analytic data stacks within Databricks; experience with multi-cloud (GCP, AWS, Azure) is a significant plus.
Mandatory experience partnering with product, engineering, or growth teams and building analytic repositories from cloud billing, product telemetry, and observability data.
Senior technical expert comfortable leading data engineering projects and interfacing across product, engineering, and go-to-market teams.
Experienced operating in hyper-growth, agile SaaS organizations with global and distributed teams.
Strong outcome-driven decision maker with expertise in building data foundations that enable enterprise-scale AI-driven process intelligence.