Azure Data Engineer

EXL; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

EXL is seeking an experienced Data Engineer to design and build scalable ETL/ELT pipelines in Azure and Snowflake. You will leverage DBT and SQL to transform data from diverse sources into a reliable data warehouse, supporting insurance domain processes such as policy, claims, underwriting, and billing.

You will collaborate with data analysts, architects, and DevOps teams in a cloud-first environment, ensure data quality and governance, and optimize pipelines for performance and reliability

Qualifications

• 4+ years of data engineering experience with Azure and Snowflake.
• Proficient in Azure Data Factory for orchestrating pipelines.
• Strong SQL skills for data analysis and transformation.
• Hands-on experience with Snowflake and DBT.
• Experience with large-scale cloud data environments.

Responsibilities

• Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
• Build and maintain data integration workflows from various sources to Snowflake.
• Write efficient SQL queries for data extraction and transformation.
• Collaborate with stakeholders to translate business requirements into technical solutions, especially within insurance processes.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Maintain and enforce data quality, governance, and documentation standards.
• Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment.

Skills

Azure Data Factory

Snowflake

DBT

SQL

Data pipelines

Cloud data environments

Tools

SnowSQL

Azure Data Factory

Job description

Mandatory Skill - Azure Data Factory, DBT, Snowflake

Experience range - 5-8 yrs

Job Description:

Key Responsibilities

• Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT.
• Build and maintain data integration workflows from various data sources to Snowflake.
• Write efficient and optimized SQL queries for data extraction and transformation.
• 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.
• Monitor, troubleshoot, and optimize data pipelines for performance and reliability.
• Maintain and enforce data quality, governance, and documentation standards.
• Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment.

Must-Have Skills

• 4+ years of experience in data engineering roles using Azure and Snowflake, DBT.
• Strong experience with Azure Cloud Platform services.
• Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines.
• Proficiency in SQL for data analysis and transformation.
• Hands-on experience with Snowflake and SnowSQL for data warehousing.
• Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse.
• Experience working in cloud-based data environments with large-scale datasets.
• Strong problem-solving, communication, and collaboration skills.

Good-to-Have Skills:

• Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions.
• Familiarity with Python or PySpark for custom data transformations.
• Understanding of CI/CD pipelines and DevOps for data workflows.
• Exposure to data governance, metadata management, or data catalog tools.
• Knowledge of business intelligence tools (e.g., Power BI, Tableau).