Senior Analytics Engineer
Temporal Technologies1 month ago
Base Salary
$138k - $220k/yr
Responsibilities
- Build and maintain reusable analytical data products across multiple business domains.
- Define canonical entities, shared dimensions, data marts, metrics, grains, keys, lineage, and history behavior.
- Design and maintain the Omni semantic layer and certified Topics.
- Establish modeling, metric, documentation, and change-management standards.
- Build automated checks for freshness, completeness, uniqueness, dataset relationships, and visible failure reporting.
- Partner with Data Platform and Trust on deployment, orchestration, observability, access controls, performance, cost, and reliability.
- Partner with Data Science and Applied AI on feature tables, prediction outputs, model consumption, and monitoring.
- Translate ambiguous stakeholder questions into precise definitions, reusable models, and trusted self-service products.
- Create governed templates, sandboxes, review processes, and promotion workflows for qualified contributors.
- Contribute to architecture decisions, design reviews, code reviews, coaching, SQL and Python development, testing, and documentation.
Requirements
- Advanced SQL skills with the ability to reason about correctness, performance, and maintainability.
- Working proficiency in Python for building and maintaining jobs that create and alter data-lake tables.
- Experience with data transformation frameworks such as DBT or SQLMesh.
- Experience designing data marts using dimensional or entity-centric modeling.
- Experience implementing and maintaining a semantic layer or governed metrics.
- Advanced knowledge of grain, keys, history, lineage, contracts, and quality controls.
- Experience with Git, automated tests, CI/CD, and production ownership.
- Ability to translate ambiguous questions into reusable products and improve self-service while maintaining shared definitions.
- Experience working with senior business and technical stakeholders.
- Helpful experience includes S3, Athena, Iceberg, Hive, or another open lakehouse architecture; Omni Analytics, Looker, or a comparable semantic layer; orchestration systems; usage-based B2B SaaS, cloud infrastructure, developer tools, or consumption-based revenue; governed contribution programs; and metadata or semantic products for analytics agents.
About Temporal Technologies
Temporal Technologies builds an open-source durable workflow platform that software teams use to orchestrate long-running, stateful application logic across services. It monetizes through a managed cloud offering and commercial support for its server and SDKs. Founded in 2019 and headquartered in Bellevue, Washington, it lists public adopters such as Netflix, Snap, Indeed, and Datadog.