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Job Description

One of our Automotive customers is seeking a Data Engineer to join their growing company. We are seeking a senior‑level Data Engineer who can architect and develop from scratch. This person will design modern data pipelines, set the foundation for data governance and data quality, and enable both client‑facing and internal reporting across BI. The role requires a hands‑on builder with excellent communication skills who can present complex data topics to C‑suite and executive leadership and collaborate across claims, auditing, legal, and customer support teams nationwide.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

-7–10 years of progressive experience as a career data engineer (senior level).

-Proven experience architecting and building systems from scratch (not just iterating on existing platforms).

-ETL/ELT expertise and strong data modeling (dimensional/star/snowflake), lineage, and metadata management.

-Hands‑on proficiency with SQL and Snowflake (migration, optimization, security, governance features).

-Advanced Python for data engineering (packaging, logging, testing, performance).

Azure data stack experience (Data Factory, Databricks, Synapse/SQL, Storage, CI/CD in Azure DevOps/Git).

-Demonstrated data governance and data quality implementation (frameworks, tools, and processes).

-Exceptional communication skills and comfort presenting to C‑suite/executive leadership and external clients. -Insurance / TPA background preferred; familiarity partnering across claims, auditing, and legal functions.