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Mid-level, generalist Data Engineer in metro Pune with broad cloud and ETL requirements attracts many applicants.
Core data engineering skills are transferable, though enterprise governance and domain knowledge increase fit sensitivity.
Requires specific cloud data platform, Spark/ETL, SQL and data governance expertise, enforcing strict technical filters.
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Lead design, development, and maintenance of scalable data pipelines and large-scale data platforms to support analytics, reporting, APIs, and AI use cases across multiple enterprise domains.
Implement Data-as-a-Product principles, ensuring data assets are governed, discoverable, high-quality, and well-documented for broad self-service consumption.
Collaborate cross-functionally with Product Managers, Data Scientists, and business stakeholders to deliver AI-ready datasets and support GenAI and advanced analytics solutions.
Bachelor’s degree in Computer Science, IT, Engineering, Data Analytics, or equivalent experience.
Intermediate experience in data engineering including designing and supporting enterprise data pipelines using modern cloud data platforms and ETL/ELT technologies.
Proficiency with data modeling, SQL development, data quality validation, and scalable data architectures supporting reporting, APIs, analytics, and AI/ML.
Experience working in Agile cross-functional teams with Product Managers, Data Scientists, and Architects to deliver business outcomes.
Experienced in building and optimizing reusable data pipelines and domain-aligned data products within a Data-as-a-Product operating model including metadata, lineage, and governance.
Skilled in translating business requirements into scalable, maintainable data engineering solutions balancing quality and performance.
Familiarity or exposure to AI/ML, GenAI, vector databases, semantic search, and AI-ready data engineering practices supporting enterprise AI solutions.