Lead Software Engineer

Develop innovative solutions using Java, J2EE, Microservices, Python, Spark, Snowflake and AWS in a collaborative data engineering team for the Business Banking technology.

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

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.

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.

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

Required qualifications, capabilities, and skills:

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

Advanced knowledge of architecture, design and business processes.

Full Software Development Life Cycle experience within an Agile framework.

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

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.

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.

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

Broad and deep understanding of multiple application server platforms.

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

Integration and Continuous Deployment, DevOps models and tools.

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

Experience with Data Warehousing concepts (including Star Schema) .

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

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

Familiar with multiple Data & Analytics technology stacks.

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

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

Understanding data related security challenges.

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

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

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

Appreciation of Controls and Compliance processes for applications and data.

In depth understanding of data technologies and solutions is preferable.

Drive Process improvements and implement process changes as necessary.

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