Core Responsibilities
Data Extraction &
Ingestion:

Write complex SQL queries to pull primary data from internal data lakes, warehouses, and secondary third-party APIs.
Data Cleansing &
Validation:

Audit raw data pipelines to eliminate duplicates, resolve missing entries, and fix broken formatting before processing.
Dashboard Design &
Reporting:

Develop, refresh, and maintain automated, self-serve visualization dashboards for company stakeholders.
Trend &
Statistical Analysis:

Run diagnostic analysis using Python or R to identify historical trends, interpret KPIs, and evaluate business performance variances.

Required Technical Skills &
Toolsets An ideal candidate must be highly proficient across several distinct layers of the contemporary data stack:
Business Intelligence (BI): Mastery of interactive dashboard creation using Tableau, Power BI, or Looker.
Core Analytics:



Robust foundational knowledge of Advanced Excel (Index/Match, Power Query, pivot tables).
Database Management: Deep proficiency in SQL (PostgreSQL, MySQL, BigQuery, or Snowflake) for complex data retrieval.
Programming Languages: Hands-on experience executing data manipulation workflows via Python (Pandas, NumPy) or R.

Soft Skills and Traits
Critical Thinking: Asking the right questions of data rather than simply running queries.
Problem-Solving: The capacity to look at messy data systems, track errors, and restructure pipelines logically.

Communication: Explaining why a metric dropped or spiked without overloading stakeholders with unnecessary technical jargon

📌 Data Analytics Pune (India)
🏢 Naukri e-Hire
📍 India