Software Engineering Software Developer; Java Back-End - Data Intelligence Praha, CZ

We are seeking you, a skilled back-end software developer, to join IBM's Data Intelligence development team. We provide worldwide enterprises with high-quality software products, ensuring data is reliable, accurate, complete, trustworthy, AI-ready, and compliant with regulations. Data intelligence helps organizations discover, curate, trust, and access data through cataloging, quality assurance, governance, and lineage tracing. You will contribute to taking IBM® Manta Data Lineage to a new level, and help our customers determine data flow throughout their models and systems by increasing their data pipeline transparency.

The team:

The candidate will join the international Engineering team, based in Prague, Krakow, Lisbon, Porto, India, and the US. The team includes software developers, Dev Ops, QA engineers, App Sec, architects, and PMs.

Your role and responsibilities

What you’ll do as part of the role:

• Design, implement, integrate, test, optimize, and maintain new data lineage features and components.
• Develop data agents allowing the customers to retrieve lineage from their data sources
• Deliver features as a whole – you will not focus just on small parts, but on the complete user experience
• Utilize Java 17 and 21, Spring, Jenkins, Sonar Qube, Git Hub, and jUnit
• Discuss performance and optimize
• Write clean, stable, extensible, automation-tested, and code-reviewed code.
• Leverage agile SW development while working closely with the other developers, architects, QA engineers, Dev Ops, and product managers to refine and iterate product requirements. Maintain a no-nonsense approach within a corporate environment.
• Cooperate with the L2 support team when handling and debugging customer issues in the target environment.
• Create/maintain technical documentation.

Bachelor's Degree

Preferred education

Master's Degree

Required technical and professional expertise

• Good autonomy in Java, Spring/Spring Boot and the open-source ecosystem (Apache etc.), microservices architecture, and building RESTful APIs.
• Experienced in writing automated tests across the entire testing pyramid routinely - from atomic unit tests to end-to-end tests covering the full functionality.
• Solid understanding of relational databases (we use Postgre
  
  SQL mostly) and ORMs in general (we use MyBatis)
• Ability to discuss performance, stability, and other non-functional requirements and design and implement according to it
• Previous exposure to CI&CD practices (Jenkins / Tekton, etc.)
• Advanced communication skills and ability to work collaboratively with cross-functional teams.
• Being a self-starter with excellent problem-solving skills, able to work independently and as part of a team.
• Strong sense of ownership and delivery

• Bachelor’s degree in computer science (or equivalent), or relevant background
• You understand the development process very well and are eager to suggest improvements
• Experience with supporting production software and providing L3 support
• Basic containerization knowledge (Docker, Kubernetes or Open Shift Container Platform, etc).

IBM Software infuses core business operations with intelligence—from machine learning to generative AI—to help make organizations more responsive, productive, and resilient. IBM Software helps clients put AI into action now to create real value with trust, speed, and confidence across digital labor, IT automation, application modernization, security, and sustainability. Critical to this is the ability to make use of all data, because AI is only as good as the data that fuels it.

In most organizations data is spread across multiple clouds, on premises, in private datacenters, and at the edge. IBM’s AI and data platform scales and accelerates the impact of AI with trusted data, and provides leading capabilities to train, tune and deploy AI across business. IBM’s hybrid cloud platform is one of the most comprehensive and consistent approach to development, security, and operations across hybrid environments—a flexible foundation for leveraging data, wherever it resides, to extend AI deep into a business.

In a world where technology…