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Popular mid-level analytics role with broad cloud, ETL, and BI requirements.
Core SQL, ETL and BI skills are broadly transferable across industries; domain experience optional.
Explicit 5-9 years plus mandatory SQL, cloud, ETL, and Power BI experience.
Design and implement scalable analytical solutions and enterprise reporting structures using AWS Redshift, S3, SQL, and data modeling best practices.
Build and optimize ETL workflows, ingestion pipelines, and deliver high-performing analytical data models and visualizations with Microsoft Power BI.
Drive enterprise-wide analytics initiatives, including data preparation, schema testing, data quality checks, and collaborate with business and technical teams to provide strategic insights.
5-9 years of experience with Azure/AWS, Microsoft Power BI, SQL, analytical data modeling, data visualization, and analytics engineering frameworks.
Strong hands-on expertise in end-to-end modern data warehouse build, including SQL scripting, complex query writing, stored procedures, and transformation processes.
Experience with AWS Redshift, S3, ETL pipelines, Slowly Changing Dimensions (SCD), Change Data Capture (CDC), dimensional and relational modeling techniques.
Work Experience Required: 5-9 years
Experienced analytics engineer with a track record of building scalable enterprise data products and implementing modern data warehouse solutions.
Proficient in SQL performance tuning and optimization, with solid understanding of data modeling concepts and analytics architecture.
Preferably has domain experience in Insurance Analytics or Financial Analytics and familiarity with insurance data structures and finance processes within insurance.