Data Analyst

WNS; Gurugram District; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

WNS in Gurugram, India is seeking a Data Engineer with 7+ years of experience specializing in data processing, analytics, and cloud platforms. You will analyze and process large structured datasets using SQL, Python, Pandas and PySpark, and design scalable data pipelines for analytics-ready datasets.

You will build and optimize ETL pipelines on GCP, perform data cleansing and validation, develop queries in BigQuery, and create dashboards in Tableau or Power BI.

Qualifications

• 7+ years of experience as a Data Engineer.
• Proficient in SQL, Python, Pandas and PySpark.
• Experience with cloud platforms (GCP/AWS) and data modeling.

Responsibilities

• Analyze and process large structured datasets using SQL, Python, Pandas and PySpark.
• Build, optimize and maintain data transformation pipelines for analytics-ready data.
• Perform data cleansing, validation and quality checks.
• Develop analytical queries using BigQuery and create dashboards in Tableau/Power BI.
• Integrate external data sources via APIs and web scraping; automate ingestion.
• Design, schedule and monitor pipelines with Apache Airflow.
• Deliver end-to-end analytical solutions with requirements gathering and reporting.
• Work with GCP to build scalable data architectures and analytics solutions.
• Optimize ETL pipelines and ensure data accuracy and performance.

Skills

SQL

Python

Pandas

PySpark

BigQuery

Airflow

Tableau

Power BI

Cloud platforms

Data modeling

Job description

7+ years of experience as a Data Engineer with expertise in data processing, analytics, and cloud platforms.

Analyze and process large structured datasets using SQL, Python, Pandas, and PySpark.

Build, optimize, and maintain data transformation pipelines for analysis-ready datasets.

Perform data cleansing, validation, and quality checks using regular expressions and other data validation techniques.

Develop and optimize analytical and reporting queries using Google BigQuery.

Integrate external data sources through APIs and web scraping to automate data ingestion.

Design, schedule, and monitor data pipelines using Apache Airflow.

Create interactive dashboards and reports using Tableau or Power BI.

Deliver end-to-end analytical solutions, including requirements gathering, data validation, development, and reporting.

Work with Google Cloud Platform (GCP) to build scalable data architectures and analytics solutions.

Design and optimize ETL pipelines using Big Data technologies and data modeling best practices.

Apply performance optimization techniques for large-scale data processing and analytics.

Collaborate with cross-functional teams to deliver business-focused data solutions.

Ensure data accuracy, reliability, and performance across all analytical workflows.