Data Engineer

Cardinal Health

. Develop, maintain, and support reliable data pipelines that extract, transform, and load data from multiple source systems into the data warehouse .

Posted 10/28/2026contractVaughan • CanadaMid-LevelSenior💰 CA$89,400 - CA$119,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining data pipelines, ensuring data quality and compliance while collaborating with stakeholders to deliver effective data solutions. Proficient in SQL development, data modeling, and cloud-based data platforms to support business intelligence and analytics.

Highest-signal resume keywords

SQL DevelopmentData EngineeringCloud Data PlatformsData Warehousing ConceptsData Quality Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLData TransformationData ModelingETL ProcessesPythonData IntegrationData Pipeline MonitoringRoot Cause AnalysisTechnical DocumentationData Governance

Soft Skills

Effective CommunicationCollaborationIndependent Work ManagementProblem Solving

Tools & Technologies

Google Cloud PlatformBigQueryLookerTableauPower BICelonisVersion ControlAI-Assisted Development Tools

Industry Keywords

Healthcare AnalyticsPharmaceutical AnalyticsSupply Chain AnalyticsCommercial AnalyticsData Orchestration

Tech Stack

Tools & technologies

AWSAzureBigQueryCloudETLGoogle Cloud PlatformPythonSQLTableau

About the role

Key responsibilities & impact

Develop, maintain, and support reliable data pipelines that extract, transform, and load data from multiple source systems into the data warehouse
Build and maintain scalable data models that promote data consistency, accuracy, performance, and accessibility
Automate recurring data-processing activities and improve existing workflows
Partner with analysts and business stakeholders to understand data requirements and deliver solutions
Perform source-to-target analysis, document transformation rules and data lineage, reconcile results, and identify root causes of data discrepancies
Write, test, and optimize SQL queries, transformations, and data-processing logic
Apply data security, privacy, governance, and compliance standards
Monitor data pipelines, investigate failures and data-quality issues, perform root-cause analysis, and implement corrective and preventive actions
Create and maintain technical documentation for data assets, processes, dependencies, and operational procedures
Participate in code reviews, testing, deployment activities, and continuous improvement of data engineering practices
Collaborate with senior engineers, analysts, business stakeholders, source-system teams, and engineering teams

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, or a related field, or equivalent practical experience, preferred
5+ years of experience in data engineering, data integration, SQL development, or a related technical field, preferred
Strong SQL skills and experience developing, testing, and troubleshooting data transformations
Working knowledge of data warehousing concepts, dimensional data modeling, and ETL or ELT processes
Experience developing or supporting data solutions on at least one cloud-based data platform, such as Google Cloud Platform, Amazon Web Services, or Microsoft Azure
Experience using version control and participating in structured development, testing, and deployment practices
Ability to analyze data issues, identify root causes, and implement practical solutions
Effective written and verbal communication skills, with the ability to collaborate across technical and business teams
Ability to manage assigned work independently while seeking guidance on complex or ambiguous problems
Experience with Python or another programming language used for data processing, automation, testing, or integration
Experience using AI-assisted development tools responsibly with appropriate validation of generated outputs
Experience with Google Cloud Platform, BigQuery, or comparable cloud data technologies
Experience supporting business intelligence tools such as Looker, Tableau, or Power BI
Experience integrating, modeling, or preparing data for process mining platforms such as Celonis or similar solutions
Experience working with SAP data structures, master and transactional data, and enterprise business processes
Exposure to data orchestration, data quality, metadata management, or CI/CD practices
Knowledge of machine learning, generative AI, agentic AI, and supporting data architectures
Experience in healthcare, pharmaceutical, distribution, supply chain, or commercial analytics environments

Benefits

Comp & perks

Hybrid work model
Employment equity and inclusive workplace
Accommodation throughout the hiring process for applicants with disabilities
Diversity and inclusion support