Lead Business Operations Data Engineer

Quantinuum

Lead Business Operations Data Engineer at Quantinuum, the quantum computing systems company. Building governed pipelines, analytics models, and executive dashboards for resource planning and platform performance.

Posted 8/12/2026full-timeBroomfield • Colorado, New Mexico • 🇺🇸 United StatesSenior💰 $146,000 - $183,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in data engineering and analytics, with a strong focus on building and maintaining ETL/ELT pipelines, data models, and executive-facing reporting. Proficient in advanced SQL, cloud data platforms, and delivering self-service analytics solutions for informed decision-making.

Highest-signal resume keywords

Advanced SQL ProficiencyETL/ELT Pipeline DevelopmentData Modeling and Analytics EngineeringCloud Data Warehouse ExperienceStrong Communication Skills

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringAnalytics EngineeringBusiness IntelligenceETL/ELT Pipeline DevelopmentSQLPythonData Quality TestingDimensional ModelingAnalytics Dashboard CreationData Integration Solutions

Soft Skills

Cross-Functional CollaborationCommunication SkillsInfluencing Technical StandardsIdentifying InsightsRecommending Improvements

Tools & Technologies

Power BITableauGrafanaDbtAirflowDagsterPrefectAzure Data Factory

Industry Keywords

SOX ComplianceOperational AnalyticsData GovernanceData LineageAuditabilityPerformance TuningSystem Reliability MetricsResource Demand Planning

Tech Stack

Tools & technologies

AirflowAzureCloudETLGrafanaPythonSQLTableau

About the role

Key responsibilities & impact

Partner with the Platform technical team and Offering Management on resource demand planning and capacity analytics, including platform systems usage, census forecasting, and materials and services needs
Analyze and report on machine uptime, throughput rates, job success/failure rates, and customer commitment fulfillment
Build and maintain time reporting and census analytics, auditing data for completeness and accuracy
Own platform usage reporting, including SOX-compliant financial reporting, active user and project counts, system reliability indicators, and feature adoption metrics
Design, develop, and maintain scalable ETL/ELT pipelines from operational systems and enterprise tools
Implement monitoring, observability, and alerting for data pipelines and platform health
Architect and implement robust data models and data integration solutions
Transform raw data into analytics-ready tables and semantic layers using dbt or similar frameworks
Maintain and evolve data warehouses and reporting layers
Ensure data accuracy, lineage, documentation, and auditability
Partner with engineering and platform teams on data architecture, governance, access patterns, integrations, and engineering practices
Deliver self-service analytics dashboards and datasets
Communicate insights through narratives, visuals, and recommendations for technical and non-technical audiences
Own the data analytics strategy and roadmap for resource forecasting and platform usage
Provide authoritative reporting and BI dashboards for leadership investment decisions

Requirements

What you’ll need

Bachelor’s degree minimum
Minimum 8+ years of experience in data engineering, analytics engineering, business intelligence, or operational analytics
Experience owning data pipelines, data models, and executive-facing reporting in a business-critical environment
Must be a U.S. Person: U.S. citizen, permanent resident or green card holder, or worker granted asylum or refugee status
Must not be a People's Republic of China national or Russian national unless also a U.S. citizen
Advanced SQL proficiency, including complex joins, window functions, analytical modeling, query optimization, and performance tuning
Experience designing, building, and maintaining production-grade ETL/ELT pipelines and analytical models
Experience with Python or another scripting language
Experience with cloud data warehouses, data platforms, or Lakehouse environments
Experience with analytics engineering, dimensional modeling, semantic layers, reusable metrics, and self-service analytics
Experience with Git-based workflows, code review, documentation, and repeatable deployment practices
Experience with data quality testing, validation, monitoring, lineage, and auditability
Experience building leadership dashboards and reports
Strong communication skills and cross-functional collaboration
Ability to define and influence technical standards for data systems
Experience delivering varied analytics
Familiarity with Power BI, Tableau, Grafana, or equivalent
Experience with dbt or similar analytics engineering frameworks
Experience with Airflow, Dagster, Prefect, Azure Data Factory, or equivalent
Experience supporting SOX, financial, compliance, or audit-sensitive reporting
Experience analyzing system reliability, usage, or operational performance metrics
Ability to identify insights and recommend improvements
Experience optimizing data platforms for performance, cost, reliability, scalability, and observability
Safety-sensitive placement requires a pre-employment drug test

Benefits

Comp & perks

A competitive salary and innovative, game-changing work
Flexible work schedule
Employer subsidized health, dental, and vision insurance
401(k) match for student loan repayment benefit
Equity
401k retirement savings plan
12 Paid holidays
Generous vacation + sick time
Paid parental leave
Employee discounts