Java and Python Developer

NTT Data, Inc.

$110K — $130K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years of software engineering experience or equivalent
  • Strong hands-on experience with Java full stack, Kafka, and Python
  • Ability to apply AI-assisted development practices at scale
  • Experience using AI-powered engineering tools
  • Solid understanding of end-to-end SDLC and Agile/DevOps delivery models
  • Proficiency with source control systems and CI/CD pipelines
  • Foundation knowledge of databases, APIs, and system integrations

Responsibilities

  • Lead complex technology initiatives and deliverables
  • Design, code, test, debug, and document software solutions
  • Apply AI-first engineering mindset for code generation and reviews
  • Drive adherence to engineering best practices and compliance
  • Investigate and resolve technical issues with traditional and AI-assisted methods
  • Mentor junior engineers and share knowledge on technology and AI tools
  • Communicate technical status and recommendations clearly

Benefits

  • Opportunities for continuous learning, especially in emerging technologies
  • Collaborative work environment with experienced team members
  • Access to advanced AI-powered engineering tools
  • Support for professional development and leadership growth
  • Contributions to significant technology initiatives that impact the business
Full Job Description
Req ID: 389836
We are currently seeking a Java and Python Developer to join our team in Charlotte, North Carolina (US-NC), United States (US).

Job Description:
In this role, you will:
  • Lead moderately complex initiatives and deliverables within technical domain environments
  • Contribute to large scale planning of strategies
  • Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments
  • Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures
  • Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements
  • Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals
  • Lead projects and act as an escalation point, provide guidance and direction to less experienced staff
Required Qualifications:
  • 7+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:
  • Approximately 7 + years of professional experience in software engineering or application development with a proven track record of delivering production-quality systems
  • Strong hands-on experience with Java full stack, Kafka, Python, and frameworks aligned with the team's technology stack
  • Demonstrated ability to apply AI-assisted development practices at scale to improve engineering productivity, code quality, and reliability
  • Practical experience using AI-powered engineering tools (e.g., code assistants, automated testing tools, documentation generators, observability and troubleshooting assistants, or internal AI platforms)
  • Solid understanding of the end-to-end software development life cycle (SDLC) and hands-on experience working in Agile / DevOps delivery models
  • Advanced proficiency with source control systems, CI/CD pipelines, and modern development workflows, including AI-augmented reviews and automation
  • Experience supporting deployments, upgrades, environment stability, and production operations, including on-call or incident support
  • Strong foundational knowledge of databases, APIs, distributed systems, messaging platforms, and system integrations
  • Good awareness of security, risk, data privacy, compliance, and responsible AI usage, with the ability to apply these principles in design and implementation
  • Ability to independently troubleshoot and resolve moderately complex technical issues, leveraging documentation, system telemetry, and AI-assisted insights
  • Demonstrated commitment to continuous learning, especially emerging AI technologies and patterns relevant to the engineering domain
  • Strong communication skills with the ability to collaborate effectively with engineers, product partners, and stakeholders, and to mentor junior team members

Job Expectations:
  • Lead and contribute to moderate to high-complexity technology initiatives, including new feature development, system enhancements, upgrades, and deployments
  • Design, implement, test, debug, and document robust solutions, making informed architectural decisions within established guidelines
  • Apply an AI-first engineering mindset, proactively using approved AI tools for code generation, refactoring, reviews, testing, troubleshooting, and documentation while ensuring compliance with enterprise standards
  • Drive adherence to engineering best practices, design patterns, coding standards, and responsible AI and data-usage policies
  • Identify, propose, and help implement improvements to service quality, performance, stability, scalability, and developer efficiency
  • Independently investigate and resolve recurring and non-trivial technical issues, leveraging both traditional debugging techniques and AI-assisted analysis, and lead resolution efforts to meet SLAs
  • Ensure security, compliance, and risk controls are embedded into design, development, and support activities, including appropriate handling of sensitive data when using AI tools
  • Actively participate in and lead code reviews and technical design discussions, providing clear, constructive feedback
  • Mentor and support junior engineers, sharing knowledge on technology, domain context, and effective use of AI tools
  • Build strong domain expertise in the assigned business area and help identify AI use cases that create measurable technical or business impact
  • Communicate technical status, risks, trade-offs, and recommendations clearly to team members and stakeholders
  • Demonstrate ongoing growth in technical leadership, decision-making, system ownership, and responsible AI usage

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