Senior Director of Software Engineering

Join us to shape the future of data and analytics at a leading global financial institution. As a hands-on leader with expertise in software engineering, cloud, and data technologies, you will mentor teams and drive innovation. Your experience with AWS, Databricks, Terraform, Agile methodologies, and enterprise product release management is essential and highly valued The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly. As the Senior Director of Software Engineering at JPMorgan Chase within Corporate – AIML Data Platforms and Chief Data & Analytics, you will lead the development and delivery of innovative data and analytics solutions that promote the firm’s commercial success. In this strategic role, you will oversee large-scale projects, mentor technical teams, and collaborate with product, technology, and data partners to advance our cloud data platforms and engineering practices. Job Responsibilities Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Oversee the delivery of large-scale projects, coordinating efforts across multiple teams and stakeholders to ensure timely and successful outcomes. Collaborate with product, technology, and data partners to develop and execute strategic data engineering initiatives. Mentor and guide technical teams, fostering a culture of continuous learning and excellence in software engineering practices. Solves the companies most challenging cloud data platform problems by building innovative technical solutions around Data Lake Tools. Designs, implements, and maintains a managed AWS Databricks platform, and provides engineering and operational support for the platform to SRE and app teams. Performs platform design, set-up and configuration, workspace administration, resource monitoring, providing engineering support to data engineering teams, Data Science/ML, and Application/integration teams. Develops secure high-quality production code, and reviews and debugs code written by others Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies Required qualifications, capabilities, and skills Formal training or certification onsoftware engineeringconcepts and 10+ years applied experience. In addition,5+ years of experience leading technologists to manage, anticipate and solve complex technical items within your domain of expertise and more broadly across the organization Hands-on experience with Python and/or Java application program development with use of automated unit testing Hands-on practical experience delivering system design, application development, testing, and operational stability Hands-on practical experience with terraform development and understanding of terraform enterprise. Hands-on experience with GitHub / Bitbucket code versioning tool, Jenkins build tool and pypi / maven artifactory integrations Knowledge of Big Data distributed compute frameworks like Spark. Preferred qualifications, capabilities, and skills Exposure to AWS & Databricks Platform administration Experience with Agile development processes, as needed (SCRUM/KANBAN) using JIRA. Experience in Data pipelines using Spark Experience in managing product release lifecycle at enterprise level.

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