Sr. Data Engineer

Required Skills & Experience

7+ years of experience as a Data Engineer\nStrong SQL experience with the ability to write, troubleshoot, and optimize complex queries\nExperience building and supporting ETL/ELT pipelines using Azure Data Factory or similar data orchestration tools\nStrong understanding of data modeling concepts, including:\nStar schema design\nFact and dimension tables\nType 1 and Type 2 Slowly Changing Dimensions\nOLTP vs. OLAP data structures\nExperience building reports and dashboards in Power BI or a similar BI/reporting tool\nExperience working with Snowflake and/or Coalesce, including building tables, developing transformations, and troubleshooting query performance\nExperience partnering with business stakeholders to translate reporting and analytics requirements into technical solutions

Nice to Have Skills & Experience

Experience deploying an AI project in Snowflake

Job Description

Insight Global is seeking a Senior Data Engineer to join a growing analytics and data engineering team focused on enterprise reporting, analytics, and modern data platform initiatives. This individual will sit within the Data Strategy group, but will part of a team that supports the Employee Benefits group. They will partner closely with business stakeholders, product owners, business analysts, and fellow engineers to deliver scalable data solutions and business insights. On a day-to-day basis, this person will design and optimize data warehouse solutions within Snowflake, build and maintain ELT pipelines utilizing technologies such as Azure Data Factory, Fivetran, and Coalesce, and develop dimensional data models that support enterprise reporting and analytics. They will troubleshoot and optimize complex SQL queries, analyze source systems, perform data mapping activities, and ensure data quality and reliability across multiple business domains. Additionally, this individual will support reporting initiatives through tools such as Sigma and Power BI, participate in data governance and engineering standards efforts, evaluate emerging technologies and AI-driven capabilities, and serve as a technical mentor by conducting code reviews and promoting data engineering best practices across the organization. The ideal candidate is comfortable owning data solutions from ingestion through reporting and has the ability to effectively communicate with both technical and business stakeholders.