Data Engineer Snowflake

EXL; Gurugram District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

EXL is seeking a data engineer to design, build, and maintain scalable data pipelines, migrating legacy architectures to cloud-ready AI data platforms and developing semantic layers for analytics.

You will collaborate with stakeholders, data scientists, analysts, and product teams to translate data requirements into robust solutions, ensuring data quality and governance across environments. Proficiency with Python, PySpark, Snowflake, and BI tools is expected.

Qualifications

• Degree in Economics, Statistics, Engineering or related quantitative field.
• 2+ years hands-on Python & PySpark with tuning and optimization.
• Experience with data lakes, lakehouses, and data warehouses (Snowflake/Databricks/BigQuery/Redshift).
• Snowflake certification (SnowPro Core) required; SnowPro Advanced preferred.
• Strong communication to explain technical concepts to non-technical audiences.
• Experience supporting AI/ML pipelines and feature engineering.
• Experience with Tableau/Power BI/Looker for data visualization.
• Hands-on cloud experience with AWS, Azure, or GCP.

Responsibilities

• Design, build, and maintain robust data pipelines for analytics and AI/ML use cases.
• Lead migration of legacy data architectures to cloud-based, AI-ready platforms.
• Develop semantic layers for business-friendly data access for analytics tools.
• Collaborate with stakeholders, data scientists, analysts, and product teams to translate requirements.
• Ensure data quality, integrity, security, and governance best practices.
• Document data architectures, pipelines, and best practices for knowledge sharing.

Skills

Python

PySpark

Data modelling

ETL design

SQL

Cloud platforms

Snowflake

BI tools

Communication

Education

Bachelor's/Master's in quantitative field

Tools

Snowflake

Databricks

BigQuery

Redshift

Tableau

Power BI

Job description

This role involves building data pipelines, migrating legacy architecture to AI ready data & semantic layer, collaborating with stakeholders, and optimizing data workflows to support advanced analytics and business intelligence initiatives.

Responsibilities

Key Responsibilities

• Design, build, and maintain robust, scalable, and reliable data pipelines to support analytics, reporting, and AI/ML use cases
• Lead the migration of legacy data architectures to modern, cloud-based, AI-ready data platforms
• Develop and implement semantic layers to enable consistent, business-friendly access to data for analytics and BI tools
• Collaborate closely with business stakeholders, data scientists, analysts, and product teams to understand data requirements and translate them into technical solutions
• Ensure data quality, integrity, security, and compliance through validation, monitoring, and governance best practices
• Document data architectures, pipelines, and best practices to support knowledge sharing and long-term maintainability

Qualifications

• Bachelors / Master's degree in Economics, Statistics, Engineering or a related quantitative field from a top-tier university
• Advanced Python & Pyspark: 2+ years of hands-on experience with performance tuning and complex query optimization
• Hands-on experience with modern data architectures such as data lakes, lakehouses, and data warehouses such as Snowflake, Databricks, BigQuery, or Redshift
• Snowflake certification (SnowPro Core required; SnowPro Advanced preferred)
• Excellent communication skills, with the ability to explain technical concepts to non-technical audiences
• Experience supporting AI/ML pipelines and feature engineering
• Working knowledge of data visualization software such as Tableau, Power BI and Looker
• Hands-on experience with cloud platforms: AWS, Azure, or GCP.