Aryaveer Kumar

Data Analyst

India 1+ yrs exp 84 · Excellent

About

Data Analyst with 2+ years of experience transforming large, complex datasets into actionable business insights and analytics-ready solutions. Proficient in SQL, Python, Power BI (DAX), Alteryx, Databricks, and Azure, with hands-on experience in data transformation, validation, reconciliation, forecasting, and KPI dashboarding. Skilled in building automated data pipelines, developing scalable analytical datasets, optimizing data processing, and delivering reliable reporting solutions that improve data accuracy, efficiency, and decision-making for cross-functional stakeholders.

Skills & Expertise (32)

SQL Intermediate

7.6/10

Years Exp

Python Intermediate

7.6/10

Years Exp

Azure Databricks Intermediate

7.4/10

Years Exp

PySpark Intermediate

7.4/10

Years Exp

Power BI Intermediate

7.2/10

Years Exp

Azure Data Factory Intermediate

7.0/10

Years Exp

Docker Intermediate

6.6/10

Years Exp

Data Integration Intermediate

6.4/10

Years Exp

Dimensional Data Modeling Intermediate

6.4/10

Years Exp

Data Warehousing Intermediate

6.4/10

Years Exp

Excel Intermediate

6.2/10

Years Exp

Tableau Intermediate

6.0/10

Years Exp

Looker Intermediate

5.8/10

Years Exp

AWS Athena Intermediate

5.6/10

Years Exp

AWS Glue Intermediate

5.6/10

Years Exp

GCP Intermediate

5.6/10

Years Exp

AWS Redshift Intermediate

5.6/10

Years Exp

AWS S3 Intermediate

5.6/10

Years Exp

Alteryx Intermediate

5.4/10

Years Exp

MySql Intermediate

5.4/10

Years Exp

Postgresql Intermediate

5.4/10

Years Exp

Oracle Intermediate

5.4/10

Years Exp

YAML Beginner

4.0/10

Years Exp

CSS Beginner

4.0/10

Years Exp

HTML Beginner

4.0/10

Years Exp

C++ Beginner

4.0/10

Years Exp

Git GitHub Airflow Apache Kafka Azure Synapse Bash

Work Experience

Data Analyst

Genpact

Oct 2024 - Jul 2026

Built and maintained scalable data pipelines for pharmaceutical safety analytics using Python, SQL, PySpark, and Azure Databricks, processing adverse-event and product-batch data into structured, analytics-ready datasets for downstream reporting and real-time analysis. Designed data processing workflows integrating pharmaceutical product, batch, adverse-event, and regional datasets, applying transformation, cleansing, standardization, and dimensional data modeling to ensure consistent datasets for safety and risk analysis. Performed data profiling and validation using SQL and Python (Pandas) across product, transaction, sales, and operational datasets, identifying missing values, duplicates, and inconsistencies before dashboards reducing downstream data quality issues by catching errors upstream. Developed distributed data-processing solutions using PySpark and Databricks to optimize query logic and transformation performance on large pharmaceutical datasets, supporting scalable analytical workloads and faster stakeholder insights. Created Power BI dashboards and Excel reporting solutions using DAX and Power Query to monitor adverse-event trends, sales performance, return rates, product/channel performance, and regional risk indicators, enabling stakeholders to identify emerging safety concerns and commercial opportunities through self-service analysis. Orchestrated data workflows using Apache Airflow and Azure Data Factory with scheduled execution, dependency management, and failure handling-ensuring reliable data movement from ingestion through analytics and reducing manual intervention. Collaborated with business and analytical stakeholders to translate pharmaceutical data requirements and business rules into implementable solutions; used Git/GitHub and Docker to maintain reproducible workflows and support deployment of data-processing components.