Tower Lead
Must Have Technical/Functional Skills
Data Bricks , EBT , Airflow , Asset Management exp
Roles & Responsibilities
We are seeking a highly experienced EDO (Enterprise Data Office) Program Level Tower Lead to drive large-scale enterprise data transformation initiatives within the Asset Management domain. The ideal candidate will possess strong leadership capabilities with deep expertise in Databricks, dbt, Azure, AWS, Data Governance, Data Engineering, and Modern Data Platforms. The role requires ownership of end-to-end delivery of the Data Tower, including strategy, architecture, execution, stakeholder management, governance, and program oversight across multiple workstreams supporting investment, operations, risk, compliance, and client reporting functions.
Key Responsibilities
Program Leadership & Governance
- Lead the Data Tower within enterprise-wide EDO transformation programs.
- Define and execute data strategy aligned with business and technology objectives.
- Manage multiple delivery teams across data engineering, analytics, governance, and cloud platforms.
- Drive program planning, budgeting, resource management, and delivery governance.
- Establish KPIs, SLAs, risk management frameworks, and program health reporting.
- Present program status and strategic recommendations to C-level stakeholders.
Data Platform & Architecture Leadership
- Lead the design and implementation of modern data platforms leveraging: Databricks Lakehouse Architecture, Azure Data Platform, AWS Data Services, DBT Transformation Framework.
- Define scalable architecture patterns for batch, streaming, and real-time analytics workloads.
- Establish enterprise data standards, best practices, and reusable frameworks.
Asset Management Domain Enablement
- Drive data initiatives supporting: Portfolio Management, Investment Research, Trading & Order Management, Performance & Attribution, Risk Analytics, Compliance & Regulatory Reporting, Client Reporting, Security Master & Reference Data Management.
- Collaborate with business stakeholders to define data products and business capabilities.
Data Engineering Leadership
- Lead development of enterprise-grade data pipelines using Databricks and cloud-native technologies.
- Define ELT/ETL frameworks utilizing dbt and modern data engineering methodologies.
- Ensure high-quality delivery through automation, CI/CD, testing, and observability practices.
- Optimize data processing costs and performance across cloud environments.