Lead Software Engineer

As a Lead Software Engineer at JPMorganChase within CCB, 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. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job responsibilities

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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.

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Develops secure high-quality production code, and reviews and debugs code written by others.

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Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.

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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.

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Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies.

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Adds to team culture of diversity, opportunity, inclusion, and respect.

Required qualifications, capabilities, and skills:

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Formal training or certification on software engineering concepts and 10+ years applied experience.

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Advanced knowledge of architecture, design and business processes.

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Full Software Development Life Cycle experience within an Agile framework.

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Strong technical development experience on effectively writing code, code reviews, best practices on configuration management and code refactoring.

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Communication skills – must possess strong verbale and written communication skill and must be comfortable with fast-paced environment. Strong professional presence with the ability to interact and influence colleagues at all levels in the business; able to collaborate in team environment with team members, business leads and partners.

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Individual must have excellent problem-solving and time management and organizational skills to handle multiple projects and priorities; must be able to quickly and effectively respond to rapidly changing business needs; must be a proactive self-starter.

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Expert-level implementation skills with Java, AWS, Database technologies, Python, Scala, Spark, Snowflake.

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Broad and deep understanding of multiple application server platforms.

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Build and Release skills using Bitbucket, GitHub, Jenkins, Maven etc.

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Integration and Continuous Deployment, DevOps models and tools.

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Experience with the development and decomposition of complex SQL (RDMS Platforms).

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Experience with Data Warehousing concepts (including Star Schema) .

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Practical experience in delivering projects in Data and Analytics, Big Data, Data Warehousing, Business Intelligence. Familiar with relevant technological solutions and industry best practices.

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Good understanding of data engineering challenges and proven experience with data platform engineering (batch and streaming, ingestion, storage, processing, management, integration, consumption).

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Familiar with multiple Data & Analytics technology stacks.

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Aware of various Data & Analytics tools and techniques (e.g. Python, data mining, predictive analytics, machine learning, data modelling, etc.)

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Experience with data visualization, aware of various tools and technologies.

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Understanding data related security challenges.

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Experience with one or more leading cloud providers (AWS/Azure/GCP).

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Ability to work fast and quickly ramp up on new technologies and strategies.

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Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals.

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Appreciation of Controls and Compliance processes for applications and data.

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In depth understanding of data technologies and solutions is preferable.

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Drive Process improvements and implement process changes as necessary.

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Knowledge of industry-wide Big Data technology trends and best practices.