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Tier-1 brand, metro roles, and mid-level generalist title increase applicant density.
Core data engineering skills are transferable, but consulting experience raises domain-specific expectations.
Explicit 6–10 years, mandatory tech skills and consulting background create strict screening.
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Design, develop, and deploy enterprise-scale data engineering solutions and architect concurrent data processing pipelines.
Lead requirement discussions, prepare technical architecture, resolve ambiguities, and guide junior team members throughout full project lifecycle.
Manage scrum meetings, deliverable reviews, and collaborate with global cross-functional teams ensuring quality and timely delivery.
6-10 years of technology consulting experience with hands-on Python development and data pipeline architecture.
Strong knowledge of OOPS, exception handling, concurrency, error handling for batch sizes 1-10 GB, DB connectivity, data transformation.
Experience with RESTful API design, Git source control, and service-oriented architecture integrations.
BE/B.Tech/MCA/M.Sc (CS) or equivalent degree from an accredited university.
Experienced in leading data engineering projects involving concurrent data pipeline processing and scalable application design.
Capable of independently translating business requirements into technical architectures within large-scale, multi-disciplinary teams.
Familiar with debugging, unit testing, security compliance, and integration across multiple applications and services in a consulting environment.