We are looking for a analytical and detail-oriented Data Analyst to turn data into actionable business insights. In this role, you will be responsible for gathering, cleaning, and analyzing large datasets from various sources to identify trends, track key performance indicators (KPIs), and support strategic decision-making across departments.
The ideal candidate possesses strong statistical acumen, excellent problem-solving skills, and the ability to translate complex data findings into clear, compelling narratives for both technical and non-technical stakeholders.
Key Responsibilities
- Data Collection & Integration: Gather, extract, and consolidate data from multiple internal and external databases, ensuring data integrity and accuracy.
- Data Cleaning & Management: Perform data hygiene, preparation, and transformation tasks to ensure datasets are structured correctly for analysis.
- Reporting & Dashboards: Design, develop, and maintain automated business intelligence (BI) dashboards, reports, and data visualizations to track company milestones.
- Insight Generation: Analyze historical data and trends to identify business opportunities, operational inefficiencies, and customer behavioral patterns.
- Cross-Functional Collaboration: Partner with product, marketing, operations, and leadership teams to understand their data needs and provide analytical support for their initiatives.
- Ad-Hoc Analysis: Conduct deep-dive analyses on specific business problems or performance anomalies as requested by stakeholders.
Required Skills and Qualifications
- Experience: Proven professional experience working as a Data Analyst, Business Intelligence Analyst, or in a highly quantitative role.
- SQL Proficiency: Advanced knowledge of SQL to write complex queries, join tables, and extract specific datasets from relational databases.
- Data Visualization: Expertise with modern BI tools such as Tableau, Power BI, or Looker to build interactive and user-friendly dashboards.
- Analytical Software: Strong proficiency in using Python (Pandas, NumPy) or R for statistical analysis, data manipulation, and scripting.
- Spreadsheets: Advanced knowledge of Microsoft Excel or Google Sheets (e.g., VLOOKUP/XLOOKUP, Pivot Tables, advanced formulas) for quick data modeling.
- Communication Skills: Excellent verbal and written communication skills, with a proven ability to explain technical findings to a non-technical audience.
Preferred Qualifications
- Understanding of statistical concepts, hypothesis testing, and regression analysis.
- Experience working with cloud data warehouses such as Snowflake, Google BigQuery, or Amazon Redshift.
- Familiarity with data pipeline tools (dbt) or ETL processes.
- A strong analytical portfolio or GitHub repository showcasing previous data projects, visualizations, or code.
Pay: ₹43,000.00 - ₹47,000.00 per month
Benefits:
- Health insurance
- Life insurance
- Provident Fund
Work Location: In person
