Back
Mid-level analytics title, metro location, and popular 5–7 year band create high candidate competition.
Data platform and GenAI deployment skills transfer across industries but require enterprise-specific experience.
Explicit 5–7 years plus mandatory SQL, dimensional modeling, cloud platform, and LLM requirements enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own end-to-end delivery of AI and data solutions across key business domains, including discovery, prototyping, and deployment.
Collaborate directly with global business units to translate ambiguous goals into scalable AI/Data use cases and dashboards that drive operational efficiency.
Contribute to solution architecture for both traditional data pipelines and modern AI infrastructure, including dimensional data modeling and integration planning.
5–7 years of experience in data solutions and advanced analytics with proven deployment of Data and GenAI solutions in business contexts.
Bachelor’s or Master’s degree in quantitative or business-related discipline or equivalent practical experience.
Expert-level SQL skills, proven dimensional data modeling, enterprise-level cloud data platform scaling experience, and hands-on experience with LLM APIs or predictive modeling.
Familiarity with data governance concepts is mandatory.
Experienced in embedding with business units to convert complex business challenges into high-impact AI and data analytics solutions.
Skilled at leading stakeholder engagements and discovery sessions, effectively bridging technical and non-technical teams in AI adoption.
Comfortable working at the intersection of data engineering, AI technology, and business strategy with a focus on solution architecture and measurable impact.