Senior Analytics Engineer

Responsibilities

• Build and maintain reusable analytical data products across Temporal's business domains.
• Define canonical entities, shared dimensions, purpose-built marts, metric components, explicit grains, keys, lineage, and history behavior.
• Design and maintain core parts of the Omni semantic layer and certified Topics, with clear definitions for measures, dimensions, joins, and time handling.
• Establish and improve standards for modeling, metric implementation, documentation, and change management.
• Build automated checks for freshness, completeness, uniqueness, and relationships between datasets, and make failures visible to the teams that own them.
• Reduce duplicated or conflicting logic across source tables, marts, Omni workbooks, dashboards, notebooks, and analytical agents.
• Partner with Data Platform and Trust on deployment, orchestration, observability, access controls, performance, cost, and production reliability.
• Partner with Data Science and Applied AI on feature tables, prediction outputs, model consumption, and monitoring.
• Work with domain partners and senior stakeholders to turn ambiguous questions into precise definitions, reusable models, and trusted ways for teams to answer follow-up questions themselves.
• Help qualified contributors outside Data Engineering and Analytics create tables, models, notebooks, and workbooks through controlled sandboxes, templates, automated checks, review, and promotion into shared-use environments.

Languages