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Generic analytics engineer title, metro Mumbai location, and broad dbt/SQL requirements increase competition.
Core dbt, SQL, and semantic-layer skills are broadly transferable across industries.
Mandatory dbt production experience, strong SQL and data modelling enforce strict technical screening.
Design and own the transformation layer converting raw operational data into reliable analytical assets using dbt.
Build and maintain trusted data models, semantic layers, and metrics to power business reporting and dashboards.
Use AI tools (e.g., Claude Code, Codex) to accelerate development, automate routine tasks, and ensure high-quality, maintainable analytics solutions.
Proven hands-on experience with analytics engineering, data engineering, or BI engineering using dbt in production.
Strong SQL skills with complex queries including window functions, CTEs, and query performance understanding.
Experience with dimensional data modeling concepts (grain, facts, dimensions, historization).
Work Experience Required: Not explicitly mentioned in the JD
Experienced in end-to-end ownership of analytics models used by real stakeholders with demonstrated production judgment.
Comfortable collaborating cross-functionally to translate business needs into data models and iterate based on feedback.
Familiarity and practical experience using AI coding tools for enhancing analytics engineering workflows.