Data Product Manager - Vice President

As a Data Product Manager within the Securities Services Data Product Management team, you will have the exciting opportunity to work in a fast-paced and challenging environment. Your main role will be to partner with the Business to provide a comprehensive view and drive the strategy, development, and delivery of data lake solutions. Here are the key responsibilities you will be handling: - **Work on Product Strategy & Roadmap**: - Define and execute the product vision, strategy, and roadmap for the Securities Services Data Lake, aligning with business objectives and client needs. - **Technical Leadership**: - Provide hands-on guidance in data lake architecture, data ingestion, processing, and analytics, with a strong focus on Databricks. Collaborate with engineering teams to design scalable and robust solutions. - **Data Quality & Lineage**: - Champion best practices for data quality, data lineage, and metadata management. Implement frameworks and tools to ensure data integrity, traceability, and transparency across the data lake. - **Stakeholder Management**: - Engage with internal and external stakeholders, including business users, technology teams, and clients, to gather requirements and prioritize features. - **Delivery & Execution**: - Oversee end-to-end product delivery, from concept to deployment, ensuring high-quality releases and continuous improvement. - **Data Governance & Compliance**: - Ensure data quality, security, and compliance with regulatory requirements across all data lake initiatives. **Required qualifications, capabilities & skills**: - Bachelors or Masters degree in computer science, Engineering, or related field. - 10+ years of experience in product management, data engineering, or related roles, with significant exposure to data lake technologies (e.g., Databricks, Hadoop, Spark, AWS, Azure). - Hands-on experience with Databricks, including building and managing scalable data pipelines and analytics solutions. - Strong background in securities services, financial data, or capital markets. - Proven track record of delivering complex, large-scale data solutions in a hands-on capacity. - Deep understanding of data architecture, ETL processes, data quality frameworks, data lineage, and analytics platforms. - Excellent communication, stakeholder management, and leadership skills. - Experience working in global, cross-functional teams.,