Senior Analytics Engineer

Job not on LinkedIn

🔥 6 minutes ago

🇺🇸 United States – Remote

💵 $137.6k - $220k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

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Temporal Technologies

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

💼 Consulting

🏭 Manufacturing

📣 Marketing

💰 $75M Series B on 2023-02

Consulting • Manufacturing • Marketing

Temporal Technologies is a company that provides a platform for durable execution, helping developers build resilient applications by managing failures, network outages, and long-running processes. Their technology abstracts away the complexity of building scalable distributed systems, allowing developers to focus on delivering reliable systems faster. Temporal simplifies code by eliminating recovery logic, callbacks, and timers, making software more durable and fault tolerant. The platform supports a wide variety of applications, from transaction processing to applied AI, and is favored by developers for its ease of use and reliability. Temporal is open-source and offers both self-hosted and managed cloud services in multiple regions, enabling scalable, serverless application development.

📋 Description

• 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 the Omni semantic layer and certified Topics • Establish standards for modeling, metric implementation, documentation, and change management • Build automated checks for freshness, completeness, uniqueness, and dataset relationships • Reduce duplicated or conflicting logic across source tables, marts, workbooks, dashboards, notebooks, and analytical agents • 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 self-service analytical solutions • Enable qualified contributors to create tables, models, notebooks, and workbooks through controlled processes • Document contracts, metadata, ownership, quality status, and retrieval guidance for people and analytical agents • Contribute to architecture, design reviews, code reviews, coaching, SQL/code, modeling, testing, and documentation • Document analytics product ownership and identify duplicated or conflicting metric logic • Publish canonical entity and mart architecture standards • Launch governed contribution templates, automated checks, review, and promotion processes • Create certification and retirement processes for metrics, Topics, dashboards, and shared data products • Deliver an initial priority data product such as a revenue, PLG, or account-level model • Report to the Director of Data Engineering and Analytics

🎯 Requirements

• Advanced SQL experience, including correctness, performance, and maintainability • Working proficiency in Python for building and maintaining data-lake table jobs • Experience with data transformation frameworks such as DBT or SQLMesh • Data mart design using dimensional and entity-centric modeling • Experience implementing and maintaining a semantic layer or governed metrics • Advanced knowledge of grain, keys, history, lineage, contracts, and quality controls • Git, code review, automated tests, CI/CD, and production ownership • Ability to translate ambiguous questions into reusable products • Experience improving self-service while maintaining shared definitions • Experience working with senior business and technical stakeholders • Helpful: S3, Athena, Iceberg, Hive, or another open lakehouse architecture • Helpful: Omni Analytics, Looker, or a comparable semantic layer • Helpful: orchestration systems • Helpful: usage-based B2B SaaS, cloud infrastructure, developer tools, or consumption-based revenue • Helpful: building governed contribution programs • Helpful: designing metadata or semantic products for analytics agents

🏖️ Benefits

• Equity • Remote work arrangement • Reasonable accommodation for individuals with disabilities • AI interview recording/transcription with the option to opt out without impact on candidacy

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