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
In this role, you will lead sustaining and performance improvements across Teradata’s memory and execution systems, ensuring correctness, reliability, and customer trust under complex, large‑scale workloads.
You will focus on diagnosing and resolving memory‑driven system behaviors that manifest in customer‑impacting scenarios, particularly under AI‑driven and high‑concurrency workloads.
You will:
- Drive long‑term improvements by identifying systemic gaps in memory behavior and influencing design, validation, and operational practices across the platform
- Own end‑to‑end resolution and prevention of classes of customer‑impacting issues related to memory pressure, allocation, and execution‑path behavior
- Lead cross‑team technical investigations involving SQLE, PDE, OS, networking, infrastructure, and performance teams to resolve complex, system‑wide issues
- Influence engineering decisions through deep technical insights derived from real‑world system behavior under memory pressure
- Diagnose and resolve complex system behaviors driven by memory pressure, resource contention, and cross-layer execution dynamics
- Identify and resolve cases that appear as SQL Engine issues but originate in memory or execution‑layer interactions
- Provide PDE‑adjacent L4 triage and escalation support, particularly for high‑severity incidents
- Drive root cause analysis and translate field learnings into systemic engineering improvements
- Drive collaboration with System Performance Engineering to address cross-layer memory and concurrency challenges
- Develop and scale memory‑focused diagnostic playbooks and best practices across the organization
- Deliver and drive targeted code fixes and enhancements in memory‑ and PDE‑adjacent execution paths when required
Success in this role looks like:
- Drives systemic improvements that reduce recurring classes of memory- and execution-related customer-impacting issues across releases
- Significantly improves time-to-diagnosis for complex incidents involving memory pressure, resource contention, and cross-layer execution behavior
- Enables faster, more accurate, and lower-risk recovery decisions during high-severity incidents
- Improves correctness, stability, and performance of memory, allocation, and execution behavior under high-concurrency and AI-driven workloads
- Identifies and resolves root causes behind issues that appear as SQL Engine problems but originate in memory or execution-layer interactions
- Scales diagnostic capability across teams through memory-focused playbooks, best practices, and knowledge sharing
- Strengthens collaboration and alignment across SQLE, PDE, and Performance Engineering, driving coordinated solutions to cross-layer issues
- Reduces dependency on individual escalation by enabling broader team capability to diagnose and handle complex memory-related issues
Who You’ll Work With
On our team, we operate at the intersection of sustaining, performance engineering, data engine, and platform engineering.
You will work closely with:
- Sustaining and System Performance engineering teams
- SQLE and PDE engineering teams
- Storage, NOS, and execution‑path owners
- Customer support and escalation teams
This role reports into Sustaining and Performance Engineering leadership and requires strong cross‑organizational influence and collaboration.
Our team plays a critical role in:
- Protecting customer trust through consistent, high‑quality system behavior at scale
- Ensuring correctness, reliability, and performance across SQLE, memory systems, data access, and cross‑layer execution paths in production environments
- Enabling Teradata’s evolution to a cloud‑native, AI‑powered data platform through reliable, high‑performance execution of complex data and AI workloads at scale
What Makes You a Qualified Candidate
- 10+ years of experience in distributed systems, database engine, performance engineering, or large‑scale data platforms
- Strong expertise in diagnosing complex, cross‑layer issues involving memory, OS, networking, infrastructure, concurrency, and execution behavior in production environments
- Deep understanding of system internals (e.g., SQLE, PDE, or equivalent execution/runtime environments)
- Demonstrated ability to lead technical investigations and influence engineering decisions across teams
- Strong problem‑solving and communication skills in cross‑functional engineering environments
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field
What You’ll Bring
- Extensive experience with OS-level diagnostics and understanding of system resource behavior (e.g., memory, processes, I/O, scheduling)
- Strong scripting skills (e.g., Python) to develop diagnostic tools, automate analysis, and process large-scale system data
- Familiarity with networking and cloud infrastructure concepts to support end-to-end diagnosis of distributed system behavior
- Experience with database execution internals or platform runtime systems
- Strong background in memory behavior, resource management, and performance under concurrency
- Experience working on high‑severity production incidents (Sev1/Sev2)
- Familiarity with performance analysis, observability tools, and diagnostic frameworks
- Understanding of spill behavior, caching strategies, and execution‑path optimization
- Ability to distinguish between surface symptoms and underlying system causes (e.g., SQL vs memory vs execution)
- Experience translating field issues into actionable engineering improvements
- Experience working across global teams and influencing complex engineering organizations
- Ability to stay current with emerging trends in engineering, AI, and cloud-native technologies
Why We Think You'll Love Teradata
We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.
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