Azure Data Engineer with Insurance Domain knowledge.
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:
8 + 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).
Qualifications:
Bachelor’s or Master’s degree in Computer Science, Data Engineering,
Information Systems, or a related field.