Top Benefits
About the role
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 Senior Data Specialist at McKesson plays a pivotal role in designing, implementing, and optimizing the company's enterprise data infrastructure. This position is responsible for building scalable data pipelines, developing robust ETL/ELT processes, and ensuring data integrity, reliability, and compliance within a regulated environment. The role requires a combination of technical expertise and strategic thinking to enable advanced analytics, AI-driven use cases, and data-driven decision-making across the organization.
As a key member of the data engineering team, the Senior Data Specialist collaborates closely with data architects, analysts, data scientists, and governance teams to deliver scalable, reusable, and production-ready data solutions. The incumbent will also support the automation of data workflows, contribute to data standardization initiatives, and troubleshoot complex data issues, ensuring the delivery of high-quality data assets that support strategic initiatives and operational excellence.
Qualifications
The ideal candidate will possess a strong technical background with expertise in data engineering and analytics. A minimum of 7 years of relevant experience in designing and maintaining enterprise data pipelines, along with proficiency in SQL and Python, is required. Experience with cloud platforms such as Azure, and familiarity with modern data tools like Databricks, Snowflake, and Azure Data Factory, is essential. Knowledge of big data technologies, including Hadoop, Kafka, and distributed file systems, will be advantageous.
Candidates should demonstrate a solid understanding of data modeling, data architecture, metadata management, and data governance practices. Strong troubleshooting skills, the ability to optimize data processes, and experience in developing custom analytics components are critical. Effective communication, leadership capabilities, and the ability to mentor junior team members are also important qualities.
A bachelor's degree in computer science, information systems, or related fields is required; a master's degree is preferred. Experience in healthcare or other regulated industries is highly desirable, given the importance of compliance and data security in this sector.
Responsibilities
Design and implement scalable data pipelines and ETL/ELT processes to integrate complex data sources from internal and external systems, supporting both batch and real-time processing. Develop and optimize advanced SQL and Python queries to enhance data processing, performance, and analytical insights. Lead data exploration efforts, analyze requirements, and identify suitable data sources for various analytical and operational use cases. Create and maintain comprehensive metadata repositories, including data definitions, lineage, and business rules, to ensure data usability and integrity across enterprise systems. Implement data standardization, quality improvement, and governance processes to ensure compliance and reliability. Troubleshoot and resolve complex data issues, including performance tuning of databases and pipelines. Develop reusable query libraries and custom software components to support analytics, reporting, and AI/ML initiatives. Evaluate and recommend modern data tools and technologies to enhance platform capabilities and performance. Ensure adherence to security, privacy, and regulatory standards through rigorous data validation and documentation practices. Support testing, monitoring, and validation of data pipelines, including creating test cases and quality checks. Collaborate with cross-functional teams to align data solutions with enterprise architecture, governance standards, and strategic priorities. Provide technical leadership by influencing design decisions, mentoring junior staff, and promoting best practices in data engineering.
Benefits
McKesson offers a competitive compensation package as part of our Total Rewards program. Compensation is determined based on factors such as experience, skills, performance, and market conditions. The package includes base salary, annual bonuses, and potential long-term incentives. In addition to financial rewards, employees have access to comprehensive health benefits, retirement plans, paid time off, and wellness programs. We are committed to fostering a supportive and inclusive work environment that encourages professional growth and work-life balance. Opportunities for continuous learning, career advancement, and participation in innovative projects are integral parts of the McKesson experience.
Equal Opportunity
McKesson is an Equal Opportunity Employer. We provide equal employment opportunities to all applicants and employees regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We are committed to fostering an inclusive environment where everyone can thrive. If you require a reasonable accommodation during the application process, please contact us via email. Resumes or CVs submitted to this email will not be accepted. For more information on our policies, please visit our Equal Employment Opportunity page.
Not the right fit? Search for Data Specialist jobs in Canada
Similar Jobs
Top Benefits
About the role
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 Senior Data Specialist at McKesson plays a pivotal role in designing, implementing, and optimizing the company's enterprise data infrastructure. This position is responsible for building scalable data pipelines, developing robust ETL/ELT processes, and ensuring data integrity, reliability, and compliance within a regulated environment. The role requires a combination of technical expertise and strategic thinking to enable advanced analytics, AI-driven use cases, and data-driven decision-making across the organization.
As a key member of the data engineering team, the Senior Data Specialist collaborates closely with data architects, analysts, data scientists, and governance teams to deliver scalable, reusable, and production-ready data solutions. The incumbent will also support the automation of data workflows, contribute to data standardization initiatives, and troubleshoot complex data issues, ensuring the delivery of high-quality data assets that support strategic initiatives and operational excellence.
Qualifications
The ideal candidate will possess a strong technical background with expertise in data engineering and analytics. A minimum of 7 years of relevant experience in designing and maintaining enterprise data pipelines, along with proficiency in SQL and Python, is required. Experience with cloud platforms such as Azure, and familiarity with modern data tools like Databricks, Snowflake, and Azure Data Factory, is essential. Knowledge of big data technologies, including Hadoop, Kafka, and distributed file systems, will be advantageous.
Candidates should demonstrate a solid understanding of data modeling, data architecture, metadata management, and data governance practices. Strong troubleshooting skills, the ability to optimize data processes, and experience in developing custom analytics components are critical. Effective communication, leadership capabilities, and the ability to mentor junior team members are also important qualities.
A bachelor's degree in computer science, information systems, or related fields is required; a master's degree is preferred. Experience in healthcare or other regulated industries is highly desirable, given the importance of compliance and data security in this sector.
Responsibilities
Design and implement scalable data pipelines and ETL/ELT processes to integrate complex data sources from internal and external systems, supporting both batch and real-time processing. Develop and optimize advanced SQL and Python queries to enhance data processing, performance, and analytical insights. Lead data exploration efforts, analyze requirements, and identify suitable data sources for various analytical and operational use cases. Create and maintain comprehensive metadata repositories, including data definitions, lineage, and business rules, to ensure data usability and integrity across enterprise systems. Implement data standardization, quality improvement, and governance processes to ensure compliance and reliability. Troubleshoot and resolve complex data issues, including performance tuning of databases and pipelines. Develop reusable query libraries and custom software components to support analytics, reporting, and AI/ML initiatives. Evaluate and recommend modern data tools and technologies to enhance platform capabilities and performance. Ensure adherence to security, privacy, and regulatory standards through rigorous data validation and documentation practices. Support testing, monitoring, and validation of data pipelines, including creating test cases and quality checks. Collaborate with cross-functional teams to align data solutions with enterprise architecture, governance standards, and strategic priorities. Provide technical leadership by influencing design decisions, mentoring junior staff, and promoting best practices in data engineering.
Benefits
McKesson offers a competitive compensation package as part of our Total Rewards program. Compensation is determined based on factors such as experience, skills, performance, and market conditions. The package includes base salary, annual bonuses, and potential long-term incentives. In addition to financial rewards, employees have access to comprehensive health benefits, retirement plans, paid time off, and wellness programs. We are committed to fostering a supportive and inclusive work environment that encourages professional growth and work-life balance. Opportunities for continuous learning, career advancement, and participation in innovative projects are integral parts of the McKesson experience.
Equal Opportunity
McKesson is an Equal Opportunity Employer. We provide equal employment opportunities to all applicants and employees regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. We are committed to fostering an inclusive environment where everyone can thrive. If you require a reasonable accommodation during the application process, please contact us via email. Resumes or CVs submitted to this email will not be accepted. For more information on our policies, please visit our Equal Employment Opportunity page.
Not the right fit? Search for Data Specialist jobs in Canada