Job Summary:
We are seeking a Data Engineer with strong Python expertise (primary) and DBT-based ELT experience (secondary) to support data ingestion, transformation, and pipeline development for Data Analytics and Monitoring solutions within the Pricing domain. This role focuses on building scalable, automated data pipelines and enabling high-quality, analytics-ready datasets.
Key Responsibilities:
Design, develop, and maintain scalable data pipelines using Python for ingestion, transformation, and processing.
Implement and manage ELT workflows using DBT, ensuring modular, reusable, and maintainable transformations.
Build and optimize Snowflake data models, views, and transformations for analytics consumption.
Develop frameworks for handling structured and unstructured data ingestion.
Ensure data quality, validation, and consistency across multiple data systems.
Automate data workflows using Python-based utilities, SDKs, and CLI tools.
Perform monitoring, troubleshooting, and performance tuning of pipelines.
Required Skills:
Strong hands-on expertise in Python (Primary skill) for data engineering, including scripting, data processing, and pipeline development.
Experience with DBT (Secondary focus) for data transformation and modeling.
Solid understanding of ELT concepts, data pipeline architecture, and workflow orchestration.
Strong experience with SQL and complex data transformations.
Hands-on experience with Snowflake (data modeling, transformations, performance tuning).
Experience integrating with ETL/ELT tools (Informatica, DataStage, or similar).
Familiarity with data pipeline frameworks and orchestration tools.
Experience with CLI-based tools and Python SDKs for automation and migration.
Preferred Skills:
Exposure to cloud platforms (AWS/Azure/GCP) and modern data ecosystems.
Experience with advanced DBT practices (macros, testing, documentation).
Experience in Insurance domain, especially Pricing / Rating / Analytics datasets.
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