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Job Description
Structured overview of role & requirementsAbout This Role
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.
Minimum Requirements
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.
Ideal Candidate Profile
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.