Our Company:

At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.

What You'll Do

As a Staff Software Engineer in the Enterprise Data Protection (EDP) team, you will be a senior technical leader responsible for designing, building, and delivering highly scalable, reliable, and secure cloud-native data protection solutions.

This is a deeply hands-on role for an engineer who combines strong architectural and engineering depth, practical AI expertise, and an aggressive delivery mindset. You will be expected not only to solve complex technical problems, but also to drive solutions from ambiguity to production with speed, ownership, and engineering excellence.

Your responsibilities will include:

• Own architecture and technical direction for complex capabilities within the EDP platform, translating product and business requirements into scalable, maintainable, and production-ready solutions.
• Drive complex initiatives end-to-end, from technical exploration and architecture through implementation, testing, rollout, operationalisation, and production stabilisation.
• Design and build highly available, resilient, and scalable distributed systems and microservices using Java and modern cloud-native technologies.
• Provide technical leadership for EDP capabilities spanning AWS, Microsoft Azure, Google Cloud Platform (GCP), hybrid, and on-premises environments.
• Apply strong distributed-systems fundamentals to challenges involving data protection, backup and restore, large-scale data movement, orchestration, resiliency, security, and failure recovery.
• Bring practical AI expertise to engineering. Identify opportunities to use AI, generative AI, agents, and AI-assisted development to accelerate software engineering, improve product capabilities, automate operational workflows, and increase developer productivity.
• Rapidly prototype and validate AI-driven solutions, and convert successful experiments into secure, reliable, production-quality capabilities.
• Promote effective use of AI-assisted software development across design, implementation, code review, testing, debugging, documentation, and troubleshooting while maintaining appropriate engineering judgement and quality controls.
• Demonstrate an aggressive delivery mindset by breaking large problems into incremental outcomes, removing technical blockers, making pragmatic decisions, and maintaining strong execution momentum without compromising critical quality, security, or reliability requirements.
• Make thoughtful technical trade-offs between speed, scalability, reliability, maintainability, operational complexity, and business impact.
• Establish and raise engineering standards around architecture, coding, APIs, observability, testing, security, performance, deployment, and operational readiness.
• Lead technical design and code reviews and actively contribute production-quality code for critical components.
• Diagnose complex production and distributed-system issues across application, infrastructure, database, networking, and cloud layers.
• Identify architectural and technical debt proactively and drive improvements that simplify the platform and increase engineering velocity.
• Collaborate closely with architects, product managers, engineering managers, QA engineers, SRE/DevOps teams, and other engineering organisations to deliver business-critical capabilities.
• Mentor and technically influence engineers across the team, helping raise the overall engineering bar without requiring formal management authority.
• Take ownership beyond individual features by identifying gaps, challenging assumptions, proposing solutions, and driving them to measurable outcomes.

About the Team

The Enterprise Data Protection (EDP) team develops Teradata’s comprehensive data protection and migration solutions designed to support customers on their journey to the Autonomous Knowledge Platform.

Built on a modern microservices architecture, EDP delivers secure, reliable, and efficient data protection and migration capabilities while providing critical assessment, validation, monitoring, and error-detection capabilities.

The platform operates across public cloud, hybrid, and on-premises environments and is designed to provide enterprise customers with a seamless and trusted data protection experience at scale.

As a Staff Engineer within EDP, you will have an opportunity to influence both the technical evolution of the platform and how the organisation uses AI to build and operate the next generation of data protection capabilities.

What Makes You a Strong Candidate

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience.
• 8+ years of hands-on software engineering experience, with demonstrated ownership of complex enterprise or cloud-native systems.
• Strong hands-on programming expertise in Java, including object-oriented design, data structures, algorithms, concurrency, performance optimisation, and software design principles.
• Strong understanding of distributed systems, including scalability, high availability, fault tolerance, consistency, asynchronous processing, and failure-recovery patterns.
• Proven experience designing and delivering microservices and cloud-native applications using containers and technologies such as Docker and Kubernetes.
• Hands-on experience with at least one major public cloud platform, AWS, Microsoft Azure, or GCP, with an understanding of cloud compute, storage, identity, networking, security, and observability concepts.
• Strong understanding of relational databases, SQL, data management, and enterprise-scale data systems.
• Strong debugging and troubleshooting capabilities across Linux, applications, databases, networking, and distributed environments.
• Demonstrated experience taking large or ambiguous technical problems from concept to production and driving execution across multiple engineers or components.
• Hands-on experience applying generative AI and AI-assisted development techniques to real engineering problems. Candidates should be comfortable using AI beyond basic code completion, including areas such as design exploration, code generation, automated testing, debugging, documentation, operational automation, or AI-powered product capabilities.
• Strong understanding of software quality practices including automated testing, CI/CD, observability, secure development, and production readiness.
• Demonstrated ability to influence architecture and technical decisions across teams without relying on organisational authority.
• Excellent written and verbal communication skills, with the ability to clearly communicate complex technical concepts to engineering, product, and leadership audiences.
• A strong bias for action, accountability, and rapid delivery of measurable customer and business outcomes.

Preferred Qualifications

• Deep experience with AWS, Azure, or GCP, particularly storage, compute, identity, container, and data-management services.
• Experience designing or operating enterprise backup, restore, disaster recovery, data protection, replication, or large-scale data movement platforms.
• Experience building or integrating AI/ML or Generative AI capabilities, including LLM-powered applications, AI agents, Retrieval-Augmented Generation (RAG), tool/function calling, model APIs, evaluation, and production observability.
• Experience with modern AI development frameworks and platforms such as LangChain, Semantic Kernel, or equivalent technologies.
• Experience with Kubernetes, container orchestration, infrastructure automation, and cloud-native deployment patterns.
• Knowledge of security concepts such as encryption, identity and access management, secrets management, data immutability, and secure cloud architecture.
• Experience designing APIs and asynchronous/event-driven architectures.
• Experience with DevOps/SRE principles, CI/CD pipelines, telemetry, monitoring, and production operations.
• Knowledge of Teradata databases or other enterprise-grade RDBMS/data platforms.
• Demonstrated success mentoring senior engineers and raising engineering practices across a team or organisation.

#LI-PB1