
Senior Lead Software Engineer - Data / Machine Learning Operations
at J.P. Morgan
Posted 14 hours ago
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- Compensation
- Not specified
- City
- Plano
- Country
- United States
Currency: Not specified
Senior technical lead responsible for designing, building, and deploying large-scale cloud-native data and machine learning operational solutions. You will develop production-quality code, lead migration of legacy and big-data applications to cloud platforms (e.g., AWS/Databricks), and build/optimize data pipelines and monitoring/automation tools. The role includes providing technical guidance to peers and stakeholders, driving architectural and operational decisions, and advocating firmwide engineering best practices.
Location: Plano, TX, United States
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 vendors
- Develops secure and high-quality production code, and reviews and debugs code written by others
- Design and develop large-scale solutions or platforms using Cloud services (i.e. AWS) in alignment with the firm wide strategies and security controls
- Deploy and enable cloud based solutions at firm level, supporting complex analytics and day to day business operations
- Migrate legacy an big data applications at Cloud native applications with zero downtime
- Drives decisions that influence the product design, application functionality, and technical operations and processes
- Develop solutions or tools to monitor, provision components for automation or the processes, services, and reports
- Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
- Leverage your strong operational skills to develop impactful recommendations on upstream product, processes, or policy improvements that will optimize the user experience
- Influences peers and project decision-makers to consider the use and application of leading-edge technologies
- Adds to the team culture of diversity, opportunity, inclusion, and respect
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 expertise
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Good knowledge of Machine Learning modelling as an engineer
- Advanced 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
- Working experience in software development, OOPS and SDLC
- Ability to tackle design and functionality problems independently with little to no oversight
- Knowledge of the financial services industry and their TI systems
- Practical cloud native experience
- Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
- AWS certifications (e.g. Solutions Architect Associate)
- Knowledge of RAG architectures and exposure to AI/Automation technologies that improve operations
- Experience with building Data Pipelines in Spark, Tuning Spark queries
- Understands 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)




