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# AVP - Data Engineer

- **Company:** Insight Global
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Code Review, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Vault Modeling, Python (Programming Language), Software Tools, Standard Sql, SQL Databases, Workflow Management Systems, Git, Kubernetes, Data Pipelines, Databricks
- **Published:** August 15, 2026
- **Apply:** https://www.manhattanjobs.com/job.asp?id=3354574135&tx=KJ909PFK&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 5+ years of Data Engineering experience
 * Strong hands-on expertise with Python and SQL
 * Experience building data pipelines in Databricks
 * Experience working with Kubernetes
 * Strong experience with dbt
 * Experience with Dagster (or similar orchestration tools such as Airflow)
 * Strong data modeling experience (Kimball, Data Vault, Medallion, etc.)
 * Experience building and maintaining enterprise-scale ELT/ETL processes
 * Leadership, mentorship, or management experience and a desire to lead people while remaining technical
 * Strong Git, CI/CD, testing, and engineering best practices experience

## Description

A top re-insurance client is looking for a new AVP of Data Engineering. The team is looking for someone who can help mature engineering standards, improve pipeline quality, and partner closely with business stakeholders to deliver reliable data products for reporting and downstream consumers.

Day to Day

 * Lead and mentor a team of 4 data engineers while remaining hands-on with development
 * Build and maintain scalable data pipelines supporting reporting and analytics users
 * Partner closely with Data Analysts and business stakeholders to transform requirements into technical solutions
 * Oversee code reviews, development standards, testing, and best practices
 * Design and optimize data models and data products for downstream consumption
 * Work heavily with dbt, Dagster, Python, SQL, Kubernetes, and modern data engineering tools
 * Drive continuous improvement across the data engineering function and help establish technical direction for the team
 * Troubleshoot production issues and improve overall data quality and reliability


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