More jobs:
Azure Data Engineer
Job in
758078, Kanpur, Odisha, India
Listed on 2026-09-28
Listing for:
EXL
Full Time
position Listed on 2026-09-28
Job specializations:
-
IT/Tech
Data Engineering, Data Warehousing, Cloud Computing: Infrastructure & Operations, Data Analyst
Job Description & How to Apply Below
Mandatory Skill - Azure Data Factory, DBT, Snowflake
Experience range - 5-8 yrs
Location
- Noida, Gurgaon, Pune, Bangalore, Hyderabad, Chennai
Job Description:
Key Responsibilities :
o Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
o Build and maintain data integration workflows from various data sources to Snowflake.
o Write efficient and optimized SQL queries for data extraction and transformation.
o Work with stakeholders to understand business requirements—especially within insurance processes such as policy, claims, underwriting, billing, and customer data—and translate them into technical solutions.
o Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
o Maintain and enforce data quality, governance, and documentation standards.
o Collaborate with data analysts, architects, and Dev Ops teams in a cloud-native environment.
Must-Have Skills :
o 4+ years of experience in data engineering roles using Azure and Snowflake, DBT.
o Strong experience with Azure Cloud Platform services.
o Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines.
o Proficiency in SQL for data analysis and transformation.
o Hands-on experience with Snowflake and SnowSQL for data warehousing.
o Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse.
o Experience working in cloud-based data environments with large-scale datasets.
o Strong problem-solving, communication, and collaboration skills.
Good-to-Have
Skills:
o
Experience with Data Stage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions.
o Familiarity with Python or PySpark for custom data transformations.
o Understanding of CI/CD pipelines and Dev Ops for data workflows.
o Exposure to data governance, metadata management, or data catalog tools.
o Knowledge of business intelligence tools (e.g., Power BI, Tableau).
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