Data Engineer Snowflake
Hybrid Gurugram Full-time Mid-level Data Engineering
At a glance
Mid-level Data Engineering role at Fa Ewjt Saasfaprod1. Gurugram · full-time.
Pay not stated Data Engineering salary
RoleData Engineering
SeniorityMid-level
LocationGurugram
WorkplaceHybrid
EmploymentFull-time
PostedJul 24, 2026
Role brief
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain dependable data pipelines for analytics, reporting and AI/ML workloads
- Move older data architectures onto modern cloud platforms designed for AI use
- Create semantic layers that give analytics and BI tools consistent, business-friendly access to data
- Turn requirements from business, science, analytics and product teams into technical solutions
- Protect data quality and security through validation, monitoring and governance, and document pipelines and architecture
What you bring
- A quantitative degree in economics, statistics, engineering or a related field from a top-tier university
- At least two years using Python and PySpark, including tuning performance and optimizing complex queries
- Hands-on work with Snowflake or another listed data platform, plus the required SnowPro Core certification
- You can explain technical ideas clearly to people without a technical background
Who this fits
This mid-level role suits someone focused on hands-on data engineering, pipeline work and modern data architecture. It is hybrid and based in Gurugram, India.
From the employer
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.
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
- 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
Desirable Skills (Good-to-Have)
- 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.
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