Associate Data Analyst

Location: Gurgaon - Hybrid/Remote - India

Experience: 02 years (entry level)

About the Role

Were looking for an analytically strong, detail?oriented Associate Data Analyst to turn raw data into actionable insights. You will work across Python, SQL, Excel, and Power BI to build datasets, automate recurring analyses, and deliver dashboards that help stakeholders make timely, data?driven decisions.

Key Responsibilities

• Data extraction & preparation (SQL): Write performant queries, joins, CTEs, and window functions to pull, cleanse, and transform data from relational databases.
• Scripting & automation (Python): Use libraries like pandas, numpy, and pyodbc/sqlalchemy to build repeatable data pipelines, reconcile data, and produce analysis-ready tables.

• Business reporting (Power BI): Model data, author DAX measures, design interactive visuals, and publish dashboards; manage refresh schedules and data gateways.
• Advanced analysis (Excel): Build PivotTables/Charts, XLOOKUP/VLOOKUP, nested formulas, and scenario analyses; ensure spreadsheet governance and accuracy.
• Data quality & documentation: Conduct validation checks, track lineage, maintain data dictionaries, and document queries, code, and dashboard logic for reuse.
• Stakeholder collaboration: Translate business questions into analytical requirements; present findings with clear narratives and recommendations.
• Ad?hoc analytics: Support experiments, trend analyses, cohort studies, and KPI performance reviews.
• Compliance & security: Handle sensitive data responsibly, following company policies on access control, retention, and privacy.

• Bachelors degree in a quantitative field (e.g., Computer Science, Statistics, Engineering, Economics) or equivalent practical experience.
• Proficiency in Python (pandas/numpy; basics of coding best practices).
• Strong SQL (query optimization; complex joins; window functions).
• Advanced Excel (PivotTables, formulas, data cleaning).
• Hands?on Power BI (data modeling, DAX, report publishing).
• Sound understanding of descriptive statistics and data visualization principles.
• Excellent written and verbal communication; ability to explain technical topics to non?technical audiences.