Senior Data Engineer, Marketing – GTM

Amplitude

. Build and operate production data pipelines using Fivetran, dbt, and Snowflake, integrating CRM, marketing automation, advertising, product usage, and other business data .

Posted 11/12/2026full-timeSan Francisco • California • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating production data pipelines using Fivetran, dbt, and Snowflake, with a strong focus on data correctness and reliability. Proficient in developing custom API connectors and semantic layers for AI-enabled analytics, while collaborating effectively with cross-functional teams.

Highest-signal resume keywords

Data Engineering ExperienceStrong SQL SkillsHands-On Experience With Fivetran And DbtProduction Experience With SnowflakeData Modeling Fundamentals

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLPythonData ModelingAPI DevelopmentIncremental ProcessingSemantic Layer DevelopmentData Pipeline ManagementAutomated TestingQuery OptimizationData Integration

Soft Skills

Clear CommunicationCuriosityCollaboration

Tools & Technologies

FivetranDbtSnowflakeSalesforceMarketoGoogle AdsGitCI/CDAI ToolsCortex Analyst

Industry Keywords

Marketing AutomationCampaign PerformanceAttributionData GovernanceBusiness Intelligence

Tech Stack

Tools & technologies

PythonSnowflakeSQL

About the role

Key responsibilities & impact

Build and operate production data pipelines using Fivetran, dbt, and Snowflake, integrating CRM, marketing automation, advertising, product usage, and other business data
Develop custom API connectors when existing integrations do not meet requirements
Create trusted Marketing and GTM data products for campaign performance, funnel conversion, attribution, account engagement, intent scoring, and pipeline analysis
Build and maintain semantic layers defining shared business entities, relationships, dimensions, and metrics
Develop context layers for AI-enabled analytics, including business terminology, metric descriptions, synonyms, approved joins, business rules, and verified queries
Partner with Marketing Operations, Revenue Operations, Sales, Analytics, and other stakeholders to understand workflows and translate business problems into technical solutions
Own data correctness and reliability through source reconciliation, automated testing, freshness monitoring, failure alerts, root-cause analysis, and recovery procedures
Own end-to-end delivery from design and incremental development through validation, deployment, documentation, and ongoing support
Balance delivery speed with maintainability, performance, and operating cost
Raise engineering standards through code and design reviews, reusable patterns, knowledge sharing, and mentoring
Contribute improvements to the team’s technical roadmap

Requirements

What you’ll need

5+ years of relevant data engineering experience
Demonstrated ownership of complex production pipelines and data models
Strong SQL skills
Practical Python experience for integrations, automation, and data processing
Hands-on experience with Fivetran and dbt, including ingestion configuration, incremental transformations, testing, documentation, and troubleshooting
Production experience with Snowflake or Databricks, including query optimization, workload management, access controls, and cost-aware design
Experience building semantic layers with governed metric definitions, explicit data grain, entity relationships, and reusable business logic
Experience with Salesforce, Marketo, Google Ads, or similar CRM, marketing automation, and advertising platforms
Experience building context layers for business data and AI tools, including metadata, terminology, business rules, and validated examples
Strong data modeling fundamentals, including dimensional modeling, historical snapshots, slowly changing dimensions, deduplication, and incremental processing
Experience supporting Marketing or GTM data and understanding connections among leads, contacts, accounts, campaigns, activities, and opportunities
Production engineering practices using Git, code review, CI/CD, automated tests, observability, and safe deployment and recovery
Comfortable using AI tools such as Cursor, Claude, and Codex in day-to-day engineering work, with judgment about validating outputs and protecting sensitive data
Ability to shape project scope, explain tradeoffs, deliver value incrementally, and measure business impact
Clear communication, curiosity about unfamiliar systems, and collaborative work with technical and nontechnical partners
Nice to have: experience with marketing attribution, campaign influence, lifecycle marketing, account scoring, or warehouse-to-business-system activation
Nice to have: familiarity with Snowflake semantic views, Cortex Analyst, dbt Semantic Layer, or comparable semantic modeling tools
Nice to have: experience exposing governed data through APIs, MCP servers, or AI agents and evaluating AI-generated answers
Nice to have: experience using AI development tools to accelerate engineering work while maintaining code quality and data correctness

Benefits

Comp & perks

Excellent Medical, Dental and Vision insurance coverages, with 100% employer-paid premiums for employee Medical, Dental, Vision on select plans
401(k) retirement plan with an employer match of up to 1% of eligible pay each pay period up to $2,000 annually
Flexible time off
Paid holidays
Monthly wellness stipend
Monthly commuter transit/parking stipend
Quarterly learning and development stipend
New hire home office equipment stipend
12 weeks of Paid Parental Leave
Carrot Fertility Benefits/Adoption/Surrogacy support
Back-up Child Care support
Mental health and wellness benefits, including no-cost access to Modern Health coaching and therapy sessions
Employee Stock Purchase Program (ESPP)
Mentorship programs
Management training
Wellness initiatives
Charitable giving grant
Paid volunteer time off