Hiring | Data Engineer (Snowflake + Azure)
We are seeking a skilled Data Engineer with strong expertise in Snowflake, Azure Data Services, Data Warehousing, and Data Modeling. The ideal candidate will have hands-on experience building scalable data platforms, developing ETL/ELT pipelines, and delivering enterprise-grade analytics solutions.
Position: Data Engineer
Experience: 5–6 Years
Employment Type: C2C
Work Mode: Hybrid (2–3 Days/Week Onsite)
Shift Timing: 11:00 AM – 9:00 PM
Key Skills
- Snowflake Data Warehouse
- Data Engineering & Data Modeling
- Data Warehousing & Dimensional Modeling
- Azure Data Factory (ADF)
- Azure Databricks
- Azure Data Lake Storage (ADLS)
- Azure SQL Database
- Azure Synapse Analytics
- Python, PySpark, SQL
- Kafka & MongoDB
- GitHub Actions (CI/CD)
- Power BI & PowerApps
Key Responsibilities
- Design, develop, and optimize scalable ETL/ELT data pipelines
- Build and maintain enterprise data warehouse solutions using Snowflake
- Implement dimensional models and data architecture best practices
- Develop data processing solutions using Python, PySpark, and SQL
- Work extensively with Azure Data Factory, Databricks, ADLS, Azure SQL, and Synapse
- Develop real-time and streaming data solutions using Kafka
- Implement CI/CD pipelines using GitHub Actions
- Collaborate with business and technical teams to deliver high-quality data solutions
- Support reporting, analytics, and visualization initiatives using Power BI and PowerApps
Required Qualifications
- 5–6 years of experience in Data Engineering
- Strong expertise in Snowflake, Data Warehousing, and Data Modeling
- Hands-on experience with Azure Data Services and modern cloud data platforms
- Proficiency in Python, PySpark, SQL, Kafka, and MongoDB
- Experience building scalable and high-performance data solutions
- Strong analytical, problem-solving, and communication skills
Interested candidates can share their updated resume at:
Pay: ₹70,000.00 - ₹90,000.00 per month
Experience:
- Data Engineer (Snowflake + Azure): 5 years (Required)
Work Location: Remote
