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About the Role

Build and operate data foundations for infrastructure inventory and observability capabilities, ensuring an accurate, consistent, and reliable view of the platform, its ownership, and behavior.

Responsibilities

Design and build data models for infrastructure and operational data, defining canonical representations for resources, ownership, capacity, and utilization.
Integrate inventory, configuration, security, and observability data from multiple systems into a coherent, queryable view.
Keep key counts and metrics consistent across different consumers, and make data lineage, ownership, and limitations explicit.
Design data structures that are fast to query and easy to reason about at the scale of QRT’s estate.
Automate data processing, validation, and delivery, and build tooling to detect data-quality, freshness, and performance issues before consumers do.
Investigate and resolve data-quality, freshness, and performance issues, solving root causes rather than symptoms.
Collaborate closely with infrastructure, security, engineering, and observability teams to onboard new sources and improve the accuracy of the platform view.
Take ownership of systems end-to-end, and adapt the platform as scale, requirements, and underlying technologies change.

Requirements

Experience building and operating production-grade data platforms, analytical data models, or large-scale data-processing applications.
Strong SQL and dimensional or analytical data modeling experience, including the design of schemas that are maintainable, performant, and easy for consumers to reason about.
Strong Python software engineering experience, including the design of maintainable, tested production applications and scalable ETL/ELT pipelines.
Demonstrated rigor around data correctness: establishing provenance, reconciling conflicting or incomplete sources, and reasoning carefully about identity, ownership, and source of truth.
Solid working understanding of infrastructure and observability concepts, and comfort working across data, infrastructure, and observability domains.
Experience operating business-critical pipelines and diagnosing data, performance, and reliability issues in production.
Familiarity with knowledge graphs, ontologies, and taxonomies, and their application to modeling heterogeneous operational data.
A strong bias towards automating repetitive work, and pragmatism in balancing correctness, performance, and delivery.
Excellent problem-solving and communication skills, and the ability to own outcomes across research, engineering, and infrastructure teams.
A background in data science, statistics, or applied machine learning, particularly applied to incomplete, noisy, or inconsistent data, or to inferring missing information and identifying unusual behavior.
Experience with SQL-based analytical platforms, dbt, object storage, and data catalogs.
Experience with infrastructure inventory or CMDB data, ownership, and capacity/utilization modeling.
Experience with metrics, logs, and vulnerability data, and with observability tooling.
Experience with Superset or comparable BI and data-exploration tools.
Experience with Linux, containers, and GitLab CI/CD.
Experience with AWS services and cloud SDKs.

Skills

SQL
Dimensional modeling
Analytical data modeling
Python
ETL/ELT pipelines
Data provenance
Data reconciliation
Infrastructure concepts
Observability concepts
Knowledge graphs
Ontologies
Taxonomies
Automation
Problem-solving
Communication
Data science
Statistics
Applied machine learning
dbt
Object storage
Data catalogs
CMDB
Metrics
Logs
Vulnerability data
Observability tooling
Superset
Linux
Containers
GitLab CI/CD
AWS services
Cloud SDKs

Benefits

Initiatives and programs to enable employees achieve a healthy work-life balance.

About the Company

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world.
We are a technology and data driven group implementing a scientific approach to investing.
Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges.
QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors.

Equal Opportunity

QRT is an equal opportunity employer.
We welcome diversity as essential to our success.
QRT empowers employees to work openly and respectfully to achieve collective success.