Senior Data Analyst – Analytics Engineering & AI
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Job Description
Structured overview of role & requirementsAbout This Role
Translate complex business problems into scalable data models, metrics, dashboards, and actionable insights supporting enterprise decision-making.
Design and maintain a trusted semantic analytics layer for consistent business definitions, improving AI and conversational analytics understanding of enterprise data.
Collaborate with data engineering and business teams to develop ETL/ELT pipelines, AI-enabled analytics experiences, and modernize analytics toward AI-supported insights.
Minimum Requirements
Bachelor's degree in quantitative or related discipline.
6+ years experience in data analytics, business intelligence, analytics engineering, data engineering, or related fields.
Advanced SQL and Python skills, experience with cloud data warehouses (Snowflake, Teradata, Hadoop, AWS, Azure, GCP) and data modeling including semantic models and governed analytical datasets.
Work Experience Required: 6+ years; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Proven ability to bridge business problems and technical data solutions in enterprise-scale environments, focusing on analytics engineering and semantic layer development.
Experienced in building AI-ready analytics foundations supporting conversational analytics, generative AI, and advanced AI-driven analytical workflows.
Operates effectively with cross-functional stakeholders including data engineers, architects, product teams, and business leaders to deliver trusted, governed, and reusable analytics products.