Director of Engineering

What You'll Do:

We are seeking a strong technology leader as Director role to lead the strategy, development, and operation of Teradata Active Compute cloud platform. This leader will be responsible for building a highly scalable, reliable, and cost-efficient compute foundation for enterprise analytics, AI/ML, and data workloads across multiple public clouds.

Our cloud product is an enterprise-grade Teradata cloud data warehouse/analytics platform. We call it the active compute platform, which runs on AWS, Microsoft Azure, or Google Cloud, and is aimed at large, mission-critical workloads where predictable performance, governance, security, and workload management matter. Typical workloads include Enterprise data warehousing, Business intelligence and reporting, Large-scale SQL analytics, Customer/marketing analytics, Financial and operational analytics, Production ML/AI workloads, and Mixed workloads that need strong workload management.

Teradata improved its product portfolio and introduced additional compute capabilities as part of its newer Autonomous Knowledge Platform / Teradata Cloud architecture. The key idea is to have two different kinds of compute in the same governed environment rather than forcing every workload into one compute model. The product is intended for workloads that need to be available continuously and have predictable performance.

The leader we are looking for needs to help Teradata position itself not merely as a cloud data warehouse, but as an enterprise compute/data/AI platform where production and experimental workloads can coexist without compromising either performance or cost control.

Key Responsibilities:

• Own the technical strategy and roadmap for Teradata Cloud Platform.
• Lead multiple engineering teams responsible for compute orchestration, provisioning, scaling, workload management, reliability, and observability.
• Deliver a seamless experience across always-on production workloads and elastic, on-demand workloads.
• Drive cloud-native architecture across AWS, Azure, and GCP.
• Partner closely with Product, AI/ML, Data, SRE, and Customer teams to translate business and customer needs into platform capabilities.
• Establish strong standards for performance, availability, security, and cloud economics/FinOps.
• Build and develop a high-performing engineering organization and leadership team.
• Define and track platform SLOs, operational metrics, customer adoption, and unit economics.
• Leverage AI, including agentic development approaches, to accelerate engineering velocity, improve developer productivity, and drive rapid innovation across the platform.
• Maintain a strong execution focus, drive accountability and timely delivery of results, and think outside the box to solve complex technical and business challenges.

What Makes You a Qualified Candidate:

• 10+ years of experience in software, cloud infrastructure, distributed systems, or data platforms, including 5+ years leading engineering organizations.
• Proven experience building and operating large-scale, multi-tenant cloud platforms.
• Strong understanding of distributed databases, compute/storage separation, Kubernetes, orchestration, autoscaling, and workload management.
• Experience with both always-on production systems and elastic/serverless compute architectures.
• Strong understanding of enterprise data, analytics, AI/ML, and cloud platforms.
• Demonstrated ability to connect deep technical strategy with product direction, customer value, and business outcomes.
• Experience across AWS, Azure, and/or GCP preferred.
• Experience leveraging AI-powered development tools, agentic AI, or AI-driven engineering workflows to accelerate software development, increase engineering productivity, and enable rapid innovation.
• A strong track record of execution, with the ability to turn strategy into measurable outcomes, challenge conventional thinking, and develop creative solutions to complex problems. This is a hard requirement.

The ideal leader we are looking for is a hands-on technical leader who combines deep distributed systems expertise with strong product and organizational leadership. They should be comfortable operating at the architecture level while also building teams, managing execution, and shaping the long-term strategy for enterprise cloud compute. This leader must embrace AI-driven development as a catalyst for engineering velocity and innovation, while fostering a results-oriented culture that encourages creative thinking, experimentation, and continuous improvement.

Skills

Cloud Infrastructure, Data Platforms, Distributed Databases, Distributed Systems, Kubernetes, Software