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# Data Engineer Lead

- **Company:** Artech
- **Location:** Irvine, CA, United States
- **Experience:** Expert
- **Salary:** $93,600.0 - $104,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Big Data, Continuous Integration, Information Engineering, Extract Transform Load (ETL), DevOps, Performance Tuning, Systems Development Life Cycle, System Availability, Apache Spark, Infrastructure as Code (IaC), Functional Dependencies, Data Management, Data Delivery, Data Pipelines, Databricks
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-lead-irvine-ca--7584dd1d-3826-4913-bec6-9ccc3a8c73c7

## About the Role

Investment Management, Asset Management, Data Management, Service Level Agreement (SLA), Data Quality, Scalable System Development, Cross-Functional, High Availability, Production Support, Technical Leadership, This role requires coordination between onshore, nearshore, and offshore teams

 * Strong experience with Databricks, DBT, Apache Spark, and performance tuning.
 * Expertise in Apache Airflow/Astronomer for workflow orchestration and DAG design.
 * Deep understanding of Data Engineering, ETL/ELT, and large-scale data platforms.
 * Experience with CI/CD, DevOps, Infrastructure as Code (IaC), and automation.
 * Strong platform management, monitoring, and incident management experience.
 * Excellent leadership and stakeholder management skills.
Preferred Domain Experience:

 * Asset Management
 * Investment Management
 * Capital Markets
 * Portfolio & Market Data Platforms
EXPERIENCE REQUIRED: 8+

## Description

We are seeking an experienced Data Engineering Tower /Pod Lead with a strong background in Asset Management to lead enterprise-scale data engineering initiatives. The ideal candidate will be responsible for end-to-end data delivery, platform stability, and managing multiple data engineering pods while ensuring alignment with business and investment management objectives., * Lead and manage the Data Engineering Tower, overseeing multiple teams and delivery pods.

 * Own end-to-end data platform delivery, operational excellence, and SLA adherence.
 * Drive scalable data pipeline development, data quality, and platform reliability.
 * Manage cross-functional dependencies, stakeholder communication, and issue escalations.
 * Ensure high availability, monitoring, alerting, and production support readiness.
 * Collaborate with business, portfolio management, and technology leadership teams.
Define and implement best practices for platform governance, operational readiness, and performance optimization