Business Operations Data Engineer

Job Description

Job Title: Lead Business Operations Data Engineer. Location: Broomfield, Colorado, USA; Albuquerque, New Mexico, USA; or Brooklyn Park, Minnesota, USA

Work arrangement: On-site, with potential for up to 2 remote days per week with approval

Responsibilities:

  • Lead the design, delivery, and evolution of data analytics supporting resource planning, capacity management, and operational performance.
  • Partner with the Platform technical team and Offering Management on resource demand planning and capacity analytics.
  • Analyze platform usage, census forecasting, materials and services requirements, and performance against plan.
  • Analyze machine uptime, throughput, job success and failure rates, and customer commitment fulfillment.
  • Build and maintain time reporting and census analytics while auditing data for completeness and accuracy.
  • Own platform usage reporting, including SOX-compliant financial reporting and performance metrics;
  • Track active users, active projects, system reliability, feature adoption, and engagement metrics.
  • Design, develop, and maintain scalable ETL and ELT pipelines for operational and enterprise data.
  • Implement monitoring, observability, and alerting for data pipelines and platform health.
  • Proactively identify and resolve data reliability issues.
  • Architect robust data models and data integration solutions using industry best practices.
  • 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, governance, and auditability;
  • Partner with engineering and platform teams on data architecture, governance, access patterns, integrations, and engineering standards.
  • Deliver trusted dashboards and datasets that enable self-service analytics.
  • Communicate insights through clear narratives, visualizations, and recommendations for technical and non-technical audiences.

What You Will Own:

  • End-to-end data pipelines that transform operational data into analytics-ready and SOX-compliant datasets.
  • The platform data analytics strategy and roadmap for resource forecasting and platform usage.
  • Data quality, governance, auditability, and reporting for resource forecasting, time reporting, platform utilization, and performance metrics.
  • Authoritative BI dashboards and reporting used by leadership for resource investment decisions;
  • Data models and semantic layers designed for consistency, usability, and self-service analytics.

Qualifications:

  • Bachelor's degree or equivalent practical experience.
  • At least 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 business-critical environments.
  • Advanced SQL skills, including complex joins, window functions, analytical modeling, query optimization, and performance tuning.
  • Hands-on experience building and maintaining production-grade ETL/ELT pipelines and analytical models.
  • Experience with Python or another scripting language for data extraction, transformation, automation, testing, or analytics.
  • Experience with cloud data warehouses, data platforms, or Lakehouse environments;
  • Experience with data modeling, dimensional modeling, semantic layers, reusable metrics, and self-service analytics.
  • Experience using Git-based workflows, code review, documentation, and repeatable deployment practices.
  • Experience with data quality testing, validation, monitoring, lineage, and auditability.
  • Experience building dashboards and reports for leadership audiences;
  • Strong communication and cross-functional collaboration skills.
  • Ability to define and influence technical standards for data modeling, pipelines, documentation, testing, monitoring, and analytics.

Preferred:

  • Degree in analytics, business, engineering, computer science, or a related field.
  • Experience with BI and visualization platforms such as Power BI, Tableau, Grafana, or equivalent.
  • Experience with dbt or similar analytics engineering frameworks.
  • Experience with workflow orchestration tools such as Airflow, Dagster, Prefect, or Azure Data Factory.
  • Experience supporting SOX, financial, compliance, or audit-sensitive reporting;
  • Experience analyzing system reliability, platform usage, and operational performance.
  • Ability to proactively identify insights and recommend improvements rather than simply report data.
  • Experience optimizing data platforms for performance, cost, reliability, and scalability.
  • Experience with operational observability.
  • Comfortable working across operations, engineering, and business domains.

Benefits and Compensation:

  • Annual compensation of $146,000 to $183,000, inclusive of the bonus target.
  • Competitive compensation and opportunities to work on quantum computing technology.
  • Flexible work arrangements supporting work-life balance.
  • Employer-subsidized medical, dental, and vision insurance.
  • 401(k) retirement savings plan with company match;
  • Student loan repayment benefit.
  • Equity opportunities.
  • Generous paid time off and sick leave.
  • 12 paid holidays annually.
  • Paid parental leave.
  • Employee discount programs.

Other Information:

  • Candidates must meet U.S. Person requirements due to contractual obligations. Eligible individuals include U.S. citizens, permanent residents or green card holders, and workers granted asylum or refugee status.
  • Due to U.S. Government national security requirements, candidates cannot be nationals of the People's Republic of China or Russia unless they are also U.S. citizens.
  • Safety-sensitive positions require a pre-employment drug test.
  • Applications are accepted on an ongoing basis with no stated application deadline;
  • Quantinuum is an equal opportunity employer.
  • Quantinuum may use AI tools during parts of its recruitment process, but final hiring decisions are made by humans.
  • Reasonable adjustments are available during the recruitment process for candidates who require them.

JOB TYPE

Full-time

COMPENSATION

$146k - $183k

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