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Job Description – Data Engineer (Snowflake, dbt, Airflow, Insurance Domain)

Position: Data Engineer

Rank- Senior

Experience: 5–8 years

Employment Type: Full-time

Overview

We are seeking an experienced Data Engineer with strong expertise in Snowflake, dbt, and Astronomer- Airflow, along with a solid understanding of insurance business processes. This role will focus on building and optimizing scalable data pipelines, ensuring data quality, and enabling analytics capabilities for insurance data sets.

Key Responsibilities

• Design, develop, and maintain ELT data pipelines using Snowflake, dbt, and Airflow.
• Build and optimize data models in Snowflake to support analytics and reporting requirements.
• Implement data transformation logic in dbt for business rules and semantic layer creation.
• Automate workflows and data ingestion processes with Airflow DAGs.
• Collaborate with domain experts to translate insurance data concepts (policies, claims, underwriting) into technical pipelines.
• Monitor system performance, troubleshoot data processing issues, and optimize queries.
• Prepare documentation and conduct knowledge-sharing sessions for team members.

Required Skills

• Hands-on expertise in Snowflake for data warehousing.
• Strong proficiency with dbt for modular, testable SQL transformations.
• Solid experience with Astronomer/Apache Airflow for orchestration and scheduling.
• Strong SQL and data modelling skills.
• Knowledge of ELT best practices and performance optimization.
• Understanding of insurance data domains including policies, claims, actuarial data, and compliance.
• Familiarity with version control (Git) and CI/CD practices for data projects.
• Knowledge of Python and Git-based CI/CD pipelines is a plus.
• Knowledge of Data Vault 2.0 and building model using Dbt is a plus.

Preferred Qualifications

• Experience with cloud environments such as AWS, Azure, or GCP.
• Knowledge of Python for scripting in Airflow workflows.

Education

• Bachelor’s or master’s degree in computer science, Information Systems, Data Engineering, or related field

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