Senior Data Analyst

Overview

Cubic Transportation Systems

Company Details:

When you join Cubic, you become part of a company that creates and delivers technology solutions in transportation to make people’s lives easier by simplifying their daily journeys, and defense capabilities to help promote mission success and safety for those who serve their nation. Led by our talented teams around the world, Cubic is committed to solving global issues through innovation and service to our customers and partners.

We have a top-tier portfolio of businesses, including Cubic Transportation Systems (CTS) and Cubic Defense (CD). Explore more on Cubic.com.

Job Details:

Job Summary

The Senior Data Analyst will play a critical role within CTS’s Global Analytics function, supporting key transit programs across North America, Australia, and India. This role is accountable for transforming complex operational, performance, and customer datasets into actionable insights that drive service excellence, contractual KPI/SLA compliance, predictive decision-making, and continuous improvement.

You will work with large-scale data pipelines, develop high-quality analytical solutions, and partner closely with engineering, reporting, operations, and customer success teams to deliver data-driven outcomes for major transit agencies.

Key Responsibilities

The following are the key responsibilities of the position. It is expected that most, if not all of these, are met by the candidate:

• Develop, maintain, and optimize SQL-based datasets across Oracle and SQL Server environments, ensuring data quality, consistency, and reliability.
• Perform complex data wrangling, cleansing, modelling, and transformation required for operational analytics, KPI reporting, and performance insights.
• Build and maintain analytical datasets and scripts using Python to support automation, predictions, and advanced analysis.
• Work with large and complex datasets from multiple operational systems (ServiceNow, device telemetry, transaction data, ODS/EDW).
• Develop and maintain reports, dashboards, and data models in Power BI, including DAX, scheduled refresh, and governance-aligned practices.
• Support and enhance CTS’s KPI Engine and performance measurement frameworks, ensuring compliance with contractual KPIs and SLAs across global programs.
• Apply data science and ML concepts (e.g., classification, regression, clustering, feature engineering, model evaluation) to support predictive maintenance, anomaly detection, and optimization initiatives.
• Collaborate closely with cross-functional teams to understand requirements, translate them into analytical solutions, and deliver insights that inform decisions.
• Conduct deep-dive root-cause analysis on operational issues, device performance problems, and service incidents to support continuous improvement.
• Document analytical logic, data definitions, and technical processes following CTS governance and COE standards.
• Ensure data integrity, validation, and adherence to security and compliance requirements.
  
  
  

• Bachelor’s/master’s degree in Comp Science, Data Analytics, Engineering, Mathematics, or related field.
• 5+ years of experience in data analysis, analytics engineering, or data science roles.
• Expert-level SQL skills in both Oracle and SQL Server (complex joins, window functions, CTEs, performance tuning).
• Strong experience with Python for analytics, automation, and ML experimentation.
• Proven ability to work with very large datasets, multi-source systems, and complex business logic.
• Deep understanding of data transformation, modelling, pipelines, and ETL/ELT processes.
• Experience working with KPI/SLA-driven environments, producing measurement logic and detailed performance analysis.
• Working knowledge of Power BI (modeling, DAX, optimisation, power query etc.)
• Strong understanding of data science fundamentals including data preparation, model development workflows, and evaluation metrics.
• Ability to translate ambiguous or complex requirements into structured analytical solutions.
  
  
  

• Hands-on experience with Azure (ADF, SQL, Databricks, Data Lake) or other cloud data platforms.
• Experience working in a transportation, operations, SaaS, or managed services environment.
• Exposure to predictive maintenance, device health analytics, or operational reliability analytics.
• Familiarity with version control (Git), DevOps, CI/CD data workflows.
• Experience with data visualization best practices and storytelling techniques.
• Knowledge of ServiceNow data models (incidents, requests, tasks, changes) is an advantage.
  
  
  

Soft Skills

• Strong analytical mindset with exceptional problem-solving abilities.
• Ability to work independently and take ownership of deliverables.
• Excellent communication skills-capable of simplifying complex concepts for non-technical stakeholders.
• Comfortable working in a fast-paced, global, multi-time zone team.
• High attention to detail, data quality, and accuracy.
• Strong sense of accountability, adaptability, and continuous improvement.
• Ability to engage effectively with engineering, operations, and business stakeholders.
• Proactive, resourceful, and committed to delivering high-quality outcomes.
  
  
  

Role Impact & Success Measures

The Senior Data Analyst will directly support CTS’s global analytics capability by delivering high-quality insights, strengthening KPI/SLA measurement, and enabling data-driven decision-making across major transit programs. Success in this role is defined by strong analytical delivery, reliable data models, and meaningful contributions to operational and predictive initiatives.

Success in the First 3–6 Months

• Build a solid understanding of CTS datasets, KPI frameworks, and key operational systems.
• Deliver accurate SQL/Python transformations and enhanced Power BI reports.
• Improve data quality through validation, investigation, and documentation.
• Support program teams with timely analysis that reduces manual reporting effort.
  
  
  

Success in 6–12 Months

• Take ownership of end-to-end analytical workstreams with minimal supervision.
• Strengthen and automate KPI/SLA logic within the KPI Engine.
• Develop initial predictive analytics models (classification/regression) to support reliability or device health insights.
• Improve reporting efficiency by identifying and automating repetitive tasks.
• Build strong relationships with global stakeholders and act as a trusted analytics partner.
  
  
  

Long-Term Success (12+ Months)

• Contribute to CTS Analytics strategy, standards, and global operating model improvements.
• Become a subject matter expert in CTS operational datasets and KPI structures.
• Lead continuous improvement initiatives that enhance data quality, automation, and analytical maturity.
• Provide mentoring and technical leadership to uplift junior team members.
  
  
  

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