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AgileGrid Solutions

Data Platform Engineer

Canada

Job type: Full-time
Posting language: English
Posted: Sep 29, 2026

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Original job description

About The Company

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you.

About The Role

The Data Engineering - Level 4 role at McKesson offers a unique opportunity to lead the development and optimization of our enterprise data infrastructure. As a senior member of the data engineering team, you will be responsible for designing scalable data pipelines, developing ETL processes, and ensuring the integrity and security of data within a regulated environment. Your expertise will enable advanced analytics, support strategic decision-making, and contribute to innovative data solutions across the organization.

This position involves creating custom software components, maintaining comprehensive metadata repositories, and implementing data standardization and quality assurance processes. Collaborating closely with architects, data analysts, and data scientists, you will drive best practices in data engineering and contribute to building robust, production-ready systems that align with McKesson’s strategic objectives.

Qualifications

To succeed in this role, candidates should possess extensive experience in designing and maintaining complex data pipelines and ETL processes. Advanced proficiency in SQL and Python is essential for query optimization and data processing tasks. A strong understanding of data modeling, entity relationships, and metadata management is required. Familiarity with big data technologies such as Hadoop, Apache Kafka, and distributed file systems like HDFS is highly preferred.

Applicants should have demonstrated ability to troubleshoot complex data issues, implement data standardization processes, and develop custom software components. Effective communication and leadership skills are necessary for guiding technical teams and mentoring junior engineers. A solid understanding of data governance, security protocols, and regulatory compliance is also critical.

Responsibilities

Design and implement scalable data pipelines and ETL programs to integrate complex data sources from internal and external systems.
Write and optimize advanced SQL and Python queries to enhance data processing efficiency and performance.
Develop and maintain metadata repositories, ensuring data accuracy, integrity, and usability across enterprise systems.
Create and enforce processes for data standardization, reliability, and quality improvements across multiple platforms.
Troubleshoot and resolve complex data analytic issues, including production and development database management problems.
Develop and maintain query libraries and custom software components to support analytics and reporting functions.
Recommend and implement new tools, technologies, and best practices to improve data engineering capabilities and system performance.
Ensure compliance with governance, security, and regulatory standards through rigorous data quality checks and documentation.
Collaborate with cross-functional teams to align data solutions with enterprise architecture and business priorities.
Provide technical leadership and mentorship to junior engineering teams, promoting best practices and continuous improvement.

Benefits

McKesson offers a competitive total rewards package designed to support your professional growth and personal well-being. Our benefits include comprehensive healthcare plans, retirement savings options, paid time off, and wellness programs. We also provide opportunities for continuous learning and development, including training, certifications, and career advancement initiatives. As part of our commitment to work-life balance, flexible work arrangements and employee assistance programs are available to support your needs.

Additionally, McKesson fosters an inclusive and collaborative work environment where diversity is valued. We believe in recognizing and rewarding your contributions, ensuring you have the resources to succeed and thrive within our organization.

Equal Opportunity

McKesson is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We value diversity and inclusion and strive to create a workplace where everyone feels respected and empowered.

If you require a reasonable accommodation during the application process, please contact us by email at the designated contact addresses provided on our careers page. We encourage all qualified individuals to apply and look forward to welcoming talented professionals to our team.

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More about this job

Responsibilities

Design, build, and optimize scalable data pipelines and ETL processes, while maintaining metadata repositories and improving data quality, reliability, and security. Resolve complex data issues, develop query libraries and custom components, recommend engineering improvements, and collaborate with teams while mentoring junior engineers.

Requirements

Candidates should have extensive experience designing and maintaining complex data pipelines and ETL processes, with advanced SQL and Python skills and a strong understanding of data modeling and metadata management. Familiarity with Hadoop, Apache Kafka, and HDFS is preferred, alongside expertise in troubleshooting, governance, security, regulatory compliance, communication, and technical leadership.

Skills

Data Pipeline Design
ETL Development
SQL
Python
Data Modeling
Metadata Management
Hadoop
Apache Kafka
HDFS
Data Standardization
Data Quality Assurance
Data Governance
Data Security
Regulatory Compliance
Troubleshooting
Technical Leadership

Benefits

Healthcare Plans
Retirement Savings Options
Paid Time Off
Wellness Programs
Training And Development
Certifications
Career Advancement Opportunities
Flexible Work Arrangements
Employee Assistance Programs

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Data Pipelines
ETL
SQL
Python
Data Modeling
Entity Relationships
Metadata Repositories
Hadoop
Apache Kafka
HDFS
Distributed File Systems
Data Standardization
Data Quality Assurance
Data Governance
Data Security
Regulatory Compliance
Query Optimization
Custom Software Components
Query Libraries
Enterprise Architecture
Advanced Analytics
Data Integration
Technical Mentorship

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