Director, Product Management — Core Database Engine & AI
Teradata · Posted Nov 5
Cloud data warehousing, analytics, and enterprise artificial intelligence services
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About the role
Teradata's Autonomous Knowledge Platform unifies data, knowledge and business context so organizations can run AI-driven workloads on premises, in the cloud, or hybrid. This role leads product strategy and execution for the core database engine — the massively parallel query engine, optimizer, execution runtime, workload management, and Global Planner — including performance on native storage, cloud object storage, and open table formats like Apache Iceberg and Delta Lake. The director will also steward Teradata SQL and rethink core engine components for AI agents and GenAI/ML-driven optimization, working with engineering, AI platform, and open table format teams across the US, Europe, and India.
What you will do
- Performance: you will spend significant time inside real workloads, query plans, and benchmarks, working with engineering to deliver measurable gains release after release.
- SQL: you will be the steward of Teradata SQL, the surface customers live in, making its syntax, semantics, and ergonomics simpler, more expressive, and safer for developers, analysts, and AI agents.
- Strategy: Own the engine vision and multi-year roadmap, co-owning architecture direction with senior engineering leaders and making principled trade-offs across performance, cost, and complexity.
- AI and agents: Lead the rethink of every core engine component for AI agents as the new dominant workload, and apply GenAI and ML inside the engine to make it faster and more autonomous.
- Optimizer, execution, and workload management: Agents send many redundant queries. Explore optimizing across queries, sharing intermediate results, and returning early or approximate answers. Apply learned cardinality and cost models and LLM-assisted rewrite, with guardrails that protect plan stability. Define how workload management absorbs bursty machine traffic through agent identity, priorities, and budgets.
- Performance: Work hands-on with engineering on query plans, regressions, and bottlenecks. Own the benchmark suite and KPIs (latency, concurrency, plan stability, price-performance), including agentic workloads, and build regression gates into releases.
- Open Table formats: Own the engine side of Iceberg and Delta Lake (scan planning, pruning, pushdown, write paths) so customers never trade performance for openness. Automate statistics, clustering, and compaction with AI.
- SQL language and query interface: Design features that turn complex problems into simple, readable queries, reduce footguns while keeping power and backward compatibility, and stay aligned with ANSI SQL. Make the dialect something agents can safely generate and execute, and let agents steer with cost estimates, plan explanations, and hints.
Skills used in this role
What the employer is looking for
- 15+ years in databases, query engines, or distributed data systems, including senior product management or equivalent principal or staff engineering experience
- Expert understanding of database internals: query planning, cost-based optimization, execution models, and MPP trade-offs
- Deep SQL expertise: a heavy SQL user (data engineer, analyst, or DBA) with strong opinions on language design, ergonomics, and compatibility
- A hands-on performance mindset: reading query plans, designing benchmarks, and finding root causes with senior engineers
- A strong working understanding of LLMs and AI agents, and an informed view on how they change database design and how ML can improve database internals
- Architecture-level knowledge of Snowflake, Databricks, and ClickHouse, and fluency in lakehouse architecture and open table formats
- Degree in Computer Science or a related field; an MS or PhD in databases, distributed systems, or ML for systems is a plus
- First-principles thinking and good taste: willingness to question long-standing database assumptions, a preference for elegance over verbosity, customer obsession, daily use of GenAI tools, and the credibility to earn the trust of senior engineers
- The ability to read research critically, separate promise from hype, and design experiments to prove value, with a track record of setting multi-year platform strategy
Preferred qualifications
- A plus: experience designing SQL features or language extensions, hands-on work with optimizers or learned database components, open-source contributions, or publications at SIGMOD, VLDB, or CIDR
Benefits and support
- flexible work model
About Teradata
Teradata is a global enterprise software company specializing in multi-cloud data warehousing, analytics, and artificial intelligence solutions. Its flagship offerings, including Teradata VantageCloud and ClearScape Analytics, help organizations turn enterprise data into trusted, autonomous actions. The company serves leading global enterprises across industries such as financial services, retail, healthcare, and telecommunications.
- Industry
- Software
- Company size
- 5000-10000 employees
- Founded
- 1979
- Location
- San Diego, California, USA
- Funding stage
- Public Company
Leadership
President and Chief Executive Officer
John Ederer
Chief Financial Officer
Louis Landry
Chief Technology Officer
Sumeet Arora
Chief Product Officer
Michael Hutchinson
Chief Operating Officer
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