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Senior Analytics Engineer, AI – DX Analytics

Block

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

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

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive experience in analytics engineering and data engineering, with a strong focus on building and operating production data pipelines. Proficient in SQL, Python, and dashboard creation for non-technical stakeholders, while leveraging AI coding agents for enhanced productivity.

Highest-signal resume keywords
Analytics EngineeringSQLPythonData Pipeline DevelopmentDashboard Creation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
SQLPythonData Pipeline DevelopmentMetrics GovernanceAI Coding AgentsTypeScriptReactETL PipelinesCloud Data WarehouseDebugging Production Failures
Soft Skills
Analytical ThinkingCommunicationCollaborationProblem-Solving
Tools & Technologies
SnowflakeGitCI/CD SystemsMetrics StoreDbt Semantic LayerLookMLLLM-Based Classification Tooling
Industry Keywords
TelemetryExecutive DashboardsData InsightsAI Spend AnalysisEvent Instrumentation

Tech Stack

Tools & technologies
CloudETLPythonReactSnowflakeSQLTypeScript

About the role

Key responsibilities & impact
  • Instrument and extend raw telemetry for 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 executive-facing dashboards and visualizations
  • Analyze metrics, anticipate executive questions, and provide recommendations
  • Translate technical findings into clear executive narratives
  • Use AI coding agents to write, test, and maintain pipelines, dashboards, and analyses
  • Partner with data engineering, applied AI, and data science teams
  • Identify where AI spend is ineffective or developer friction is costly and drive improvements
  • Develop methods to quantify AI and agent productivity impact

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, with 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 (even better)
  • Ability to use AI coding agents and rigorously evaluate their output
  • Experience with TypeScript and React, governed metrics stores, and LLM-based classification tooling (technologies used and taught)

Benefits

Comp & perks
  • Remote work
  • Medical insurance
  • Flexible time off
  • Retirement savings plans
  • Modern family planning