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Senior Analytics Engineer, AI – DX Analytics

Block

. Instrument and extend raw telemetry about AI usage, code changes, CI/CD activity, and spend .

Posted 11/4/2026full-timeRemote • California • United StatesSenior💰 $139,000 - $245,400 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in analytics engineering and data pipeline management, with a strong focus on SQL and Python for building and operating data solutions. Proficient in creating executive-facing dashboards and translating complex data insights into actionable narratives for non-technical stakeholders.

Highest-signal resume keywords
SQLPythonData Pipeline ManagementCloud Data Warehouse (Snowflake)Dashboard Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
SQLPythonData Pipeline ManagementMetrics GovernanceETL ProcessesData AnalysisAI Coding AgentsTypeScriptReactGit
Soft Skills
CommunicationCollaborationProblem-Solving
Tools & Technologies
SnowflakeCI/CD SystemsMetrics StoreDbt Semantic LayerLookML
Industry Keywords
Analytics EngineeringBusiness IntelligenceTelemetry DataExecutive DashboardsAI Workflows

Tech Stack

Tools & technologies
CloudETLPythonReactSnowflakeSQLTypeScript

About the role

Key responsibilities & impact
  • Instrument and extend raw telemetry about AI usage, code changes, CI/CD activity, and spend
  • Partner with data engineers on production ETL pipelines, freshness monitoring, backfills, and alerting
  • Define and validate metrics from ambiguous or evolving signals
  • Build and ship executive-facing dashboards and visualizations
  • Analyze metrics, anticipate executive questions, and provide recommendations
  • Translate complex technical findings into clear executive narratives
  • Use AI coding agents to write, test, and maintain pipelines, dashboards, and analyses
  • Partner across data engineering, applied AI, and data science teams
  • Identify where AI spend is not paying off or developer friction is costly, and drive improvements
  • Quantify AI and agent productivity impact and help establish industry standards

Requirements

What you’ll need
  • 8+ years in analytics engineering, data engineering, or business intelligence, owning production data pipelines and insights end to end
  • Strong SQL and Python
  • Hands-on experience building and operating data pipelines against a cloud data warehouse such as Snowflake
  • Experience partnering with engineering teams to instrument new event or telemetry data
  • Experience building dashboards or internal tools that non-technical stakeholders rely on to make decisions
  • Comfort with Git, CI/CD systems, and debugging production pipeline failures such as retries and backfills
  • Experience with a metrics-governance or semantic-layer system, such as a metrics store, dbt semantic layer, or LookML is an advantage
  • AI-first workflows and thoughtful use of AI coding agents
  • Technologies include SQL (Snowflake), Python, TypeScript and React, Git, CI/CD pipelines, a governed metrics store, AI coding agents, and LLM-based classification tooling

Benefits

Comp & perks
  • Remote work
  • Medical insurance
  • Flexible time off
  • Retirement savings plans
  • Modern family planning
  • Reasonable accommodations throughout the recruitment process