Fieldguide

3 weeks ago

Senior Analytics Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Own the foundation behind analytics for Fieldguide Insights by designing the semantic layer, canonical tables, columns, and metrics that power trusted customer-facing reporting. Standardize and reconcile core metrics across sources like Amplitude, migrate production logic into governed, tested dbt models, and harden pipelines with monitoring and resilience. Partner across Product, Engineering, App Platform, and Infrastructure to support data quality, launches, and BI-to-semantic-layer migration for both traditional BI and LLM/MCP-based analytics.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Sr. Manager level

Key Responsibilities

•Design and own the Insights semantic layer with canonical definitions for tables, columns, and metrics used across reports.
•Standardize core metric definitions and reconcile them across sources such as Amplitude with documented variances.
•Migrate production report logic into governed, tested, portable dbt models and improve test coverage and reusable macros.
•Improve reliability of business-critical pipelines with proactive monitoring, alerting, and resilience to upstream schema changes.
•Partner on data quality and new environment launches, including triage, onboarding, and data handling requirements.

Pay and Benefits

Salary: USD 175,000 - 200,000 annually

Equity and Bonus:Equity

Perks:401kPaid LeaveWellness Stipend

Key Requirements

•4+ years in a modern data stack with advanced SQL and deep dbt expertise across modeling, testing, and project structure.
•Ship production-quality Python and work fluently with version control and CI while diagnosing pipeline failures end to end.
•Dimensional modeling expertise (Kimball and slowly changing dimensions) designing data models built to last as the business evolves.
•Strong data quality judgment—validating results are correct, not just computed.
•Deep experience with BigQuery and cloud data warehousing, including cost and performance optimization.

Experience:4+ years

Skills:CollaborationAnalytics judgmentData quality focusProblem-solvingReliability mindset

Tech Stack:SQLDbtPythonCIBigQueryCloud data warehousingAmplitudeVersion controlKimballDimensional modelingMCPLLMText-to-SQLSemantic layerMacrosLookerOmniTableau

Company Brief

Fieldguide

Provides an agentic AI platform that automates and manages end-to-end audit, advisory, and compliance engagements for CPA and consulting firms, improving efficiency, margins, and client outcomes.

Industry: Enterprise Software

Company Size: Medium (51 to 250 employees)

Revenue: USD 1M to 5M

Growth: Growth Stage Startup

Funding: Series B

Headquarters: San Francisco, United States

Founded: 2020

Glassdoor: 4.6

Website LinkedIn Glassdoor

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Fieldguide

3 weeks ago

Senior Analytics Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Analytics & Business Intelligence

Seniority: Sr. Manager level

Key Responsibilities

•Design and own the Insights semantic layer with canonical definitions for tables, columns, and metrics used across reports.
•Standardize core metric definitions and reconcile them across sources such as Amplitude with documented variances.
•Migrate production report logic into governed, tested, portable dbt models and improve test coverage and reusable macros.
•Improve reliability of business-critical pipelines with proactive monitoring, alerting, and resilience to upstream schema changes.
•Partner on data quality and new environment launches, including triage, onboarding, and data handling requirements.

Pay and Benefits

Salary: USD 175,000 - 200,000 annually

Equity and Bonus:Equity

Perks:401kPaid LeaveWellness Stipend

Key Requirements

•4+ years in a modern data stack with advanced SQL and deep dbt expertise across modeling, testing, and project structure.
•Ship production-quality Python and work fluently with version control and CI while diagnosing pipeline failures end to end.
•Dimensional modeling expertise (Kimball and slowly changing dimensions) designing data models built to last as the business evolves.
•Strong data quality judgment—validating results are correct, not just computed.
•Deep experience with BigQuery and cloud data warehousing, including cost and performance optimization.

Experience:4+ years

Skills:CollaborationAnalytics judgmentData quality focusProblem-solvingReliability mindset

Tech Stack:SQLDbtPythonCIBigQueryCloud data warehousingAmplitudeVersion controlKimballDimensional modelingMCPLLMText-to-SQLSemantic layerMacrosLookerOmniTableau

Company Brief

Fieldguide

Provides an agentic AI platform that automates and manages end-to-end audit, advisory, and compliance engagements for CPA and consulting firms, improving efficiency, margins, and client outcomes.

Industry: Enterprise Software

Company Size: Medium (51 to 250 employees)

Revenue: USD 1M to 5M

Growth: Growth Stage Startup

Funding: Series B

Headquarters: San Francisco, United States

Founded: 2020

Glassdoor: 4.6

Website LinkedIn Glassdoor