1 day ago

Staff Analytics Engineer, Databricks (R5493)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Own the Databricks lakehouse Gold layer and enterprise semantic layer, turning governed Silver-layer data into trusted KPIs and semantic assets. Translate approved KPI definitions into precise, testable, auditable transformation logic and enforce promotion from domain Gold to enterprise Gold with required governance sign-off. Partner with business stakeholders to resolve metric ambiguity, enable modeling standards for domain teams, review others’ models, and ensure discoverable documentation and compliance-aware access patterns.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Own Gold-layer design and delivery, including facts, dimensions, domain data marts, and governed KPI implementations on Databricks.
•Build and maintain the enterprise semantic layer with curated views, governed semantic models, metric definitions, and reusable patterns.
•Convert approved KPI/metric definitions into precise, testable, auditable transformation logic matching business meaning.
•Define and enforce the promotion path from domain Gold to enterprise Gold with business and governance sign-off.
•Partner with business stakeholders to clarify KPI definitions and enable domain teams through modeling standards, review processes, and coaching; review models for correctness and usability.

Pay and Benefits

Salary: USD 120,000 - 180,000 annually

Equity and Bonus:Equity

Key Requirements

•8+ years of experience in analytics engineering, BI engineering, or data engineering with strong dimensional modeling expertise.
•Hands-on Databricks experience, including Delta Lake and Spark SQL and/or PySpark, with familiarity with semantic-layer concepts.
•Translate ambiguous business KPI requests into precise, testable, auditable transformation logic aligned to business meaning.
•Strong SQL and data modeling fundamentals, including star schemas, fact/dimension design, and slowly changing dimensions.
•Work directly with business stakeholders to define metrics and ensure model quality and correctness.

Experience:8+ yearsDefense-techAnalytics engineeringBI engineeringData engineeringRegulated environments

Skills:Stakeholder collaborationGovernance-focused modelingData sensitivity awarenessQuality reviewAnalytics translation

Tech Stack:DatabricksDelta LakeSpark SQLPySparkSQLDbtStar schemasSlowly changing dimensions

Company Brief

Shield AI

Develops AI-powered autonomy and software for military aircraft and drones to enable autonomous ISR and combat missions, integrating perception, navigation, and mission planning for defense customers.

Industry: Defense Technology

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Funding: Series E+

Headquarters: San Diego, United States

Founded: 2015

Website LinkedIn

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Shield AI

1 day ago

Staff Analytics Engineer, Databricks (R5493)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Mid level

Key Responsibilities

•Own Gold-layer design and delivery, including facts, dimensions, domain data marts, and governed KPI implementations on Databricks.
•Build and maintain the enterprise semantic layer with curated views, governed semantic models, metric definitions, and reusable patterns.
•Convert approved KPI/metric definitions into precise, testable, auditable transformation logic matching business meaning.
•Define and enforce the promotion path from domain Gold to enterprise Gold with business and governance sign-off.
•Partner with business stakeholders to clarify KPI definitions and enable domain teams through modeling standards, review processes, and coaching; review models for correctness and usability.

Pay and Benefits

Salary: USD 120,000 - 180,000 annually

Equity and Bonus:Equity

Key Requirements

•8+ years of experience in analytics engineering, BI engineering, or data engineering with strong dimensional modeling expertise.
•Hands-on Databricks experience, including Delta Lake and Spark SQL and/or PySpark, with familiarity with semantic-layer concepts.
•Translate ambiguous business KPI requests into precise, testable, auditable transformation logic aligned to business meaning.
•Strong SQL and data modeling fundamentals, including star schemas, fact/dimension design, and slowly changing dimensions.
•Work directly with business stakeholders to define metrics and ensure model quality and correctness.

Experience:8+ yearsDefense-techAnalytics engineeringBI engineeringData engineeringRegulated environments

Skills:Stakeholder collaborationGovernance-focused modelingData sensitivity awarenessQuality reviewAnalytics translation

Tech Stack:DatabricksDelta LakeSpark SQLPySparkSQLDbtStar schemasSlowly changing dimensions

Company Brief

Shield AI

Industry: Defense Technology

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Funding: Series E+

Headquarters: San Diego, United States

Founded: 2015

Website LinkedIn