Senior Manager of Software Engineering - Big Data, Databricks

Job description

Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Senior Lead Software Engineer at JPMorgan Chase within the Consumer and Community Banking - Risk Technology Portfolio team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications. Job responsibilities: Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendorsDevelops secure and high-quality production code, and reviews and debugs code written by othersDrives adoption and governance of approved AI assisted engineering practices across teams to improve code quality, deliver speed, and operation outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patters and automation within the SDLC/TLM toolchainApplies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scaleRegularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendorsDesign and develop large-scale solutions or platforms using Cloud services (i.e. AWS) in alignment with the firm wide strategies and security controlsDeploy and enable cloud based solutions at firm level, supporting complex analytics and day to day business operationsMigrate legacy an big data applications at Cloud native applications with zero downtimeDrives decisions that influence the product design, application functionality, and technical operations and processesDevelop solutions or tools to monitor, provision components for automation or the processes, services, and reportsInfluences peers and project decision-makers to consider the use and application of leading-edge technologies Required qualifications, capabilities, and skills: Formal training and certification on software engineering concepts and 5+ years applied experience. In addition, 2+ years of experience leading technologists to manage and solve complex technical items within your domain of expertiseHands-on practical experience delivering system design, application development, testing, and operational stabilityDrives adoption and governance of approved AI assisted engineering practices across teams to improve code quality, deliver speed, and operation outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patters and automation within the SDLC/TLM toolchainApplies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scaleRegularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendorsGood knowledge of Machine Learning modelling as an engineerAdvanced in one or more programming language(s) and framework(s) (i.e., Python, Java, Big Data, Data pipeline, Machine Learning, etc.)Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)Advanced knowledge of application, data, and infrastructure architecture disciplines, and working in software development, OOPS and SDLCAbility to tackle design and functionality problems independently with little to no oversightPractical cloud native experience Preferred qualifications, capabilities, and skills: AWS certifications (e.g. Solutions Architect Associate)Knowledge of RAG architectures and exposure to AI/Automation technologies that improve operationsExperience with building Data Pipelines in Spark, Tuning Spark queriesUnderstands Python Machine Learning libraries and ecosystems (i.e., Pandas, Numpy, etc.)Working knowledge with Big Data platforms (i.e., Hadoop preferred)Experience in Cloud Technologies (i.e., AWS - Databricks preferred)