Lead Business Operations Data Engineer - 928

We are seeking a LeadBusiness Operations Data Engineer in our Broomfield, CO, OR, Albuquerque, NM Location.

Quantinuum believes that employees work better, more efficiently and more collaboratively in close proximity to other employees, where ideas can be exchanged readily, and decisions can be made more quickly for the benefit of the Company and our customers. All employees should work at their assigned location; however, this role may offer the opportunity to work remotely up to 2 days per week, with approval.

As a Lead Business Operations Data Engineer on the Analytics and Cost Estimating team within the Compute Platforms Group, you will own the design, delivery, and evolution of data analytics that inform resource planning, capacity management, and operational performance across the organization.

This is a hybrid Analytics and Data Engineering role that covers the full data lifecycle from data ingestion and pipeline management to modeling, transformation, and the creation of executive-ready BI dashboards. The role acts as a bridge between raw data infrastructure and actionable business insights, ensuring operational data is translated into reliable, decision-ready intelligence and SOX compliant where applicable.

You will partner closely with the CPG technical team, offering management, sales, finance, and business operations teams, working across enterprise systems and tools to ensure data accuracy, transparency, and measurable business impact.

All applicants for placement in safety-sensitive positions will be required to submit to a pre- employment drug test.

Key Responsibilities:

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 to support customer and R&D deliverables with performance metrics versus plan

Analyze and report on machine uptime, throughput rates, job success/failure rates, and customer commitment fulfillment to support operational reliability and planning

Build and maintain time reporting and census analytics, auditing data for completeness and accuracy and providing actionable reporting for leadership

Own platform usage reporting, including:

Platform utilization for SOX-compliant financial reporting and performance metrics

Active user and active project counts

System reliability indicators

Feature adoption and engagement metrics

Design, develop, and maintain scalable, reliable and efficient ETL / ELT pipelines that ingest data from operational systems and enterprise tools that support analytics, reporting, and operational decision-making.

Implement end-to-end monitoring, observability, and alerting data pipelines and platform health, proactively identifying and resolving data reliability issues before they impact users.

Architect and implement robust data models, and data integration solutions following industry best practices for performance, scalability, maintainability, and governance.

Model and transform raw data into analytics-ready tables and semantic layers, using analytics engineering best practices (e.g., dbt or similar frameworks)

Maintain and evolve data warehouses and reporting layers to support scalable, reliable analytics

Ensure data accuracy, lineage, documentation, and auditability, proactively resolving data quality issues

Partner with engineering and platform teams on driving data architecture standards, governance, access patterns, integrations, and engineering best practices

Deliver dashboards and datasets that enable self-service analytics while preserving consistency and trust

Communicate insights through clear narratives, visuals, and recommendations tailored to technical and non-technical audiences

What You’ll Own:

End-to-end data pipelines that ingest and transform data from operational systems into analytics-ready, SOX compliant datasets

Platform data analytics strategy & roadmap for operational resource forecasting and platform usage aligned to business priorities and decision cycles

Data quality, auditability, and governance for resource forecasting, time reporting, platform utilization, and performance metrics

Authoritative reporting and BI dashboards used by leadership to guide resource investment decisions

Data models and semantic layers designed for usability, consistency, and self-service analytics

YOU MUST HAVE:

Bachelor’s degree minimum

Minimum 8+ years of experience in data engineering, analytics engineering, business intelligence, or operational analytics, including experience owning data pipelines, data models, and executive-facing reporting in a business-critical environment.

Due to Contractual requirements, must be a US Person defined as, US citizen permanent resident or green card holder, workers granted asylum or refugee status.

Due to national security requirements imposed by the US Government, candidates for this position must not be a People's Republic of China national or Russian national unless the candidate is also a US citizen.

WE VALUE:

Bachelor’s degree in analytics, business, engineering, computer science, or a related field, or equivalent practical experience

Advanced SQL proficiency, including complex joins, window functions, analytical modeling, query optimization, and performance tuning for structured analytical datasets

Hands-on experience designing, building, and maintaining production-grade ETL/ELT pipelines, transformations, and analytical models using modern data engineering practices

Experience with Python or another scripting language for data extraction, transformation, automation, testing, or operational analytics workflows

Experience working with cloud data warehouses, data platforms, or Lakehouse environments

Experience with analytics engineering and data modeling practices, including dimensional modeling, semantic layer design, reusable metrics, and self-service analytics enablement

Experience applying version control and software development practices, including Git-based workflows, code review, documentation, and repeatable deployment practices

Experience with data quality testing, validation, monitoring, lineage, and auditability to support trusted operational, executive, and compliance reporting

Experience building dashboards and reports for leadership audiences

Demonstrated ability to validate, audit, document, and explain data to ensure trust, accuracy, transparency, and decision readiness

Strong communication skills and comfort working cross-functionally across business and technical teams

Ability to define and influence technical standards for data modeling, pipeline development, documentation, testing, monitoring, and self-service analytics

Experience with delivering a wide range of types of analytics for different contexts

Familiarity with BI and visualization tools (e.g., Power BI, Tableau, Grafana, or equivalent)

Experience with dbt or similar analytics engineering frameworks for modular transformations, testing, documentation, and governed metric definitions

Experience with workflow orchestration or scheduling tools such as Airflow, Dagster, Prefect, Azure Data Factory, or equivalent

Experience supporting SOX, financial, compliance, or audit-sensitive reporting where data lineage, controls, and repeatability are required

Experience analyzing system reliability, usage, or operational performance metrics

Ability to proactively identify insights and recommend improvements—not just report data

Comfort working in environments where data spans operations, engineering, and business domains

Experience with optimizing data platforms for performance, cost, reliability, and scalability, and operational observability

$146,000 - $183,000 a year

Compensation & Benefits:

Incentive Eligible - Range posted is inclusive of bonus target

The pay range for this role is $146,000 - $183,000 annually. Actual compensation within this range may vary based on the candidate’s skills, educational background, professional experience, and unique qualifications for the role.

Quantinuum is the world leader in quantum computing. The company’s quantum systems deliver the highest performance across all industry benchmarks. Quantinuum’s over 650 employees, including 400+ scientists and engineers, across the US, UK, Germany, and Japan, are driving the quantum computing revolution.

By uniting best-in-class software with high-fidelity hardware, our integrated full-stack approach is accelerating the path to practical quantum computing and scaling its impact across multiple industries.

By joining Quantinuum, you’ll be at the forefront of this transformative revolution, shaping the future of quantum computing, pushing the limits of technology, and making the impossible possible.

What’s in it for you?

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 and generous vacation + sick time

Paid parental leave

Employee discounts

Quantinuum is an equal opportunity employer. You will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, or veteran status. Know Your Rights: Workplace discrimination is illegal

Applications will be accepted on an ongoing basis, there is no application deadline for this position.

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