Senior Data Engineer - Asset Management

Job Title: Data Engineering POD Lead – Asset Management Location: Irvine, CA onsite Job Summar yWe are seeking an experienced Data Engineering POD Lead with a strong background in Asset Management/Investment Management to lead a high-performing data engineering pod. The ideal candidate will be responsible for end-to-end delivery of data solutions, platform reliability, and alignment with business objectives across portfolio, market, and investment data domains .Key Responsibilitie • sLead and manage the Data Engineering POD, ensuring successful project delivery and operational excellence • .Own end-to-end delivery of data engineering initiatives, maintaining SLA compliance and platform performance • .Collaborate with business stakeholders, portfolio management teams, and technology leadership • .Manage cross-team dependencies, risks, and escalations across multiple workstreams • .Design and oversee scalable data pipelines, data quality frameworks, and data platform solutions • .Ensure platform stability, monitoring, incident management, and production support readiness • .Drive best practices for reliability, availability, scalability, and operational governance .Required Skill • sStrong expertise in Databricks, Apache Spark, and performance tuning • .Hands-on experience with Apache Airflow/Astronomer for workflow orchestration and DAG design • .Extensive experience in Data Engineering, ETL/ELT, data quality, and scalable pipeline development • .Strong knowledge of DevOps, CI/CD, Infrastructure as Code (IaC), and automation • .Experience with platform administration, monitoring, alerting, and operational support • .Excellent leadership, stakeholder management, and communication skills .Preferred Domain Experienc • eAsset Managemen • tInvestment Managemen • tCapital Market • sPortfolio & Investment Data Platform • sMarket Data, Security Master, Risk & Performance Analytic • • sDomain: Asset Management / Investment Managemen • tRole: Data Engineering POD Lea • dKey Technologies: Databricks, Spark, Airflow/Astronomer, CI/CD, DevOps, Data Engineering, Platform Management, Cloud Technologies .