About this role

Every function here - growth, operations, product, client success runs on the same warehouse. When a model breaks, a definition drifts, or a dashboard goes stale, decisions across the company degrade quietly. We need an analyst who owns that layer: builds it in dbt, keeps it trustworthy as the logic underneath changes, and turns it into visibility people actually use.

This is not a report-pulling job. It is equal parts data engineering discipline and business judgement - you will be asked what the number means, not just what it is.

Key Responsibilities
- Build and maintain scalable dbt models across staging, intermediate, and smart layers with proper testing, documentation, and version control.
- Maintain and improve data products as business requirements evolve, including RevOps logic changes across models, schemas, dashboards, and MIS reporting.
- Own data structures and warehouse design for assigned domains, ensuring scalability, data freshness, quality and cost efficiency.
- Maintain data accuracy and representation across key datasets, dashboards, MIS reports,



and RevOps data flows.
- Perform SQL-based RCA across data models and key org metrics (business, growth, AI, and Voice Agent KPIs) to identify trends, root causes, performance gaps, and revenue-impacting opportunities.
- Automate recurring reports, analytics workflows, and setup alerts to reduce manual data work through scalable pipelines.
- Work with cross-functional teams to translate business questions into clear requirements, analyses, and timely insights.

Requirements
- 1+ years of relevant experience in Analytics, BI, or Data Engineering roles.
- Strong SQL skills with experience writing and optimizing queries on large relational databases.
- Solid analytical and problem-solving skills with the ability to understand complex data, schemas, ETLs, and business logic.
- Experience building dbt models for warehousing that integrate data across new and legacy infrastructure.
- Experie

📌 Data Analyst (Noida)
🏢 SquadStack.ai
📍 Noida