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# Lead Data Platform Engineering

- **Company:** i11Labs LLC
- **Location:** Addison, TX, United States
- **Experience:** Expert
- **Salary:** $140,000.0 - $155,000.0
- **Contract:** Permanent contract
- **Skills:** Automation of Tests, Microsoft Azure, Code Review, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Python (Programming Language), Azure Data Lake, Transact-SQL, Enterprise Data Management, Azure Data Factory, Snowflake, Git, Data Management, Data Pipelines
- **Published:** October 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=178d5c767363883b

## About the Role

* 6+ years of hands-on data engineering experience.
 * Strong expertise in Azure Data Factory, ADLS Gen2, and Snowflake.
 * Advanced SQL Server and T-SQL skills.
 * Experience with data modeling, dbt (or equivalent), and ETL/ELT architecture.
 * Hands-on experience with Git, CI/CD, data quality, and production monitoring.
 * Strong ownership mindset and experience leading technical initiatives.

Nice to Have: Python, Azure DevOps, and experience working with healthcare or regulated data environments.

If you're passionate about building reliable, scalable data platforms and enjoy taking technical ownership, we'd love to connect!

## Description

We're looking for a Lead Data Platform Engineer who can take end-to-end technical ownership of an enterprise data platform, from architecture and development to performance, security, and reliability.

This is a hands-on technical leadership role for someone who enjoys building scalable, production-grade data platforms, solving complex engineering challenges, and driving engineering best practices.

What You'll Do:

 * Lead the architecture, development, and operations of an enterprise data platform.
 * Build and optimize scalable ETL/ELT pipelines using Azure Data Factory, ADLS Gen2, and Snowflake.
 * Design robust data models and transformation frameworks using dbt or equivalent tools.
 * Implement CI/CD, automated testing, data quality checks, and monitoring.
 * Drive platform performance, security, cost optimization, and reliability.
 * Provide technical guidance through architecture reviews, code reviews, and mentoring.