Data Analyst

SquadStack.ai; Dadri; On-site; INR 600,000 - 1,200,000; Full time

Job summary

SquadStack.ai in India seeks an analytics/data engineering professional who owns the data layer, builds dbt models, and turns data into visible insights for growth and RevOps.

You will work across warehousing, dashboards, MIS reporting, and cross-functional teams to translate questions into analyses and timely insights that inform business decisions.

Qualifications

• 1+ years of Analytics, BI, or Data Engineering experience.
• Strong SQL skills and query optimization on large relational databases.
• Experience building dbt models and warehousing data across new and legacy infra.
• Experience investigating RCAs and resolving data discrepancies.
• Strong business judgement with using data to drive decisions and growth opportunities.
• Ability to break complex problems into executable pieces and meet deadlines.
• Preferred: dbt, Python, cloud data warehouses (Snowflake/BigQuery/Redshift), Git, A/B testing.
• Interest in conversational AI, speech data, or call-center metrics.

Responsibilities

• Build and maintain scalable dbt models across staging, intermediate, and smart layers with testing and documentation.
• Improve data products as business requirements evolve, including RevOps logic across models and MIS reporting.
• Own data structures and warehouse design for assigned domains, ensuring scalability and data quality.
• Maintain data accuracy across datasets, dashboards, MIS reports, and RevOps data flows.
• Perform SQL-based RCA to identify trends, root causes, and revenue-impacting opportunities.
• Automate recurring reports, analytics workflows, and alerts to reduce manual work.
• Collaborate with cross-functional teams to translate business questions into analyses and insights.

Skills

SQL

Analytical thinking

Problem solving

dbt

Python (preferred)

Git

Cloud warehouses

Tools

Snowflake

BigQuery

Redshift

dbt

Python

Git

Job description

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.
• Strong 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.
• Experience investigating RCAs and resolving data discrepancies.
• Strong business judgement with the ability to use data to influence decisions and identify growth opportunities.
• Ability to break complex problems into executable pieces, prioritize effectively, and deliver within timelines.
• (Preferred) Hands‑on experience with dbt, Python, cloud data warehouses (Snowflake, BigQuery, Redshift), Git, or experimentation/A‑B testing.
• (Preferred) Interest or exposure to conversational AI, speech data, voice agents, or contact‑centre metrics.