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Tier-1 brand, metro Hyderabad, popular mid-level data-engineering role with 3+ years.
Medium—core data engineering skills transfer across industries, though pharma enterprise context adds some domain specificity.
Medium—explicit 3+ years and enterprise data engineering skills required but no strict certifications.
Lead design and operationalization of scalable, reliable, and governed data pipelines integrating multiple data sources to support analytics, forecasting, AI/GenAI, and digital product capabilities.
Collaborate with GBO stakeholders, BI&T, and DS&A CoE teams to ensure data structure, quality, accessibility, and fitness for analytical and decision-support needs.
Help define and sustain data engineering standards, governance, and operational models for Hyderabad-based team deliverables.
Bachelor's degree required; Master's in Data Engineering, Computer Science, Information Systems, or related technical discipline preferred.
Minimum 3 years of experience in data engineering, analytics engineering, BI/data platforms, or related technology roles.
Demonstrated skills in enterprise data integration, pipeline development, and building scalable analytical data solutions with strong data quality and governance understanding.
Familiarity with cloud data platforms, ETL/ELT patterns, data lake/warehouse concepts, and experience working with SAP, SAP BI, Hyperion or similar enterprise analytics environments.
Experienced in cross-functional collaboration with business, analytics, and technology teams for data-driven solutions in complex enterprise environments.
Skilled in translating business and analytical requirements into scalable, governed data pipelines and data engineering architecture supporting advanced analytics and AI use cases.
Knowledgeable in data governance practices, metadata management, and operational sustainment of data engineering capabilities in a global or large-scale data environment.