Apache, Apache Spark, Asset Management, Automation, Best Practices, Capital Markets, Continuous Deployment/Delivery, Continuous Integration, Cross-Functional, Data Management, Data Quality, Database Extract Transform and Load (ETL), DevOps, High Availability, Incident Management, Investment Management, Leadership, Performance Tuning/Optimization, Production Support, Scalable System Development, Service Level Agreement (SLA), Technical Leadership
Experience: 8 years
This role requires coordination between onshore, nearshore, and offshore teams
Required Skills
- Strong experience with Databricks, 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
Job Summary
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.
Key Responsibilities
- 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.