As a Senior Director of Software Engineering - Card Data Product Technology Lead at JPMorgan Chase within the Consumer & Community Banking Card Technology team, you lead multiple technical areas, manage the activities of multiple departments, and collaborate across technical domains. Your expertise is applied cross-functionally to drive the adoption and implementation of technical methods within various teams and aid the firm in remaining at the forefront of industry trends, best practices, and technological advances.

• Leads multiple technology and process implementations across departments to achieve firmwide technology objectives
• Directly manages multiple areas with strategic transactional focus
• Provides leadership and high-level direction to teams while frequently overseeing employee populations across multiple platforms, divisions, and lines of business
• Acts as the primary interface with senior leaders, stakeholders, and executives, driving consensus across competing objectives
• Manages multiple stakeholders, complex projects, and large cross-product collaborations
• Influences peer leaders and senior stakeholders across the business, product, and technology teams
• Creates a culture of diversity, equity, inclusion, and respect for team members and prioritizes diverse representation
• Partner with product and data owner team to manage the product backlog, with accountability for clearly expressing all backlog items, user stories and acceptance criteria to best achieve product strategy

• Experience developing or leading large or cross-functional teams of technologists
• Demonstrated prior experience influencing across highly matrixed, complex organizations and delivering value at scale
• Experience leading complex projects supporting system design, testing, and operational stability
• Experience with hiring, developing, and recognizing talent
• Extensive practical cloud native experience
• Experience working with Big data technologies - Cassandra, Elastic search, document stores
• Experience working with stream processing platforms such as Kafka, Flink, Spark structured streaming
• Experience with Data Warehouses, and Analytics solutions – ETL, Store, OLAP modeling, Analytics