Design and implement scalable data pipelines and ETL/ELT programs to integrate complex data sources across internal and external systems, supporting both batch and real-time processing.
Write and optimize advanced queries using SQL and Python to improve data processing, performance, and analytical outcomes.
Lead data exploration, requirements analysis, and data source identification for analytical and operational use cases.
Develop and maintain metadata repositories, including data definitions, lineage, and business rules, ensuring data integrity and usability across enterprise systems.
Create and implement processes for data standardization, reliability, quality improvement, and governance compliance.
Troubleshoot and resolve complex data analytic issues across production and development environments, including database and pipeline performance tuning.
Develop and maintain reusable query libraries and custom software components to support analytics, reporting, and AI/ML solutions.
Recommend and implement modern tools, technologies, and best practices to enhance data engineering capabilities and platform performance.
Ensure adherence to governance, security, and regulatory compliance through rigorous data quality checks, validation processes, and documentation.
Support testing, monitoring, and validation of data pipelines, including development of test cases and quality checks.
Collaborate with cross-functional teams to align data solutions with enterprise architecture, governance standards, and business priorities.
Provide technical leadership, influence design decisions, and mentor junior engineering teams to promote best practices and continuous improvement.
Expertise in designing and maintaining scalable data pipelines, ETL/ELT processes, and data integration across complex enterprise systems.
Advanced proficiency in SQL and Python for data processing, query optimization, and analytics enablement (R is a plus).
Strong knowledge of data modeling, data architecture, metadata management, and data governance practices.
Hands-on experience with modern data platforms and tools such as Databricks, Snowflake, Azure Data Factory, and PySpark.
Familiarity with big data and distributed technologies such as Hadoop, Kafka, and distributed file systems.
Ability to implement processes for data standardization, reliability, quality improvement, and stewardship.
Competence in troubleshooting complex data issues, resolving data model conflicts, and optimizing performance.
Experience developing custom components, analytics applications, and enabling advanced analytics/AI use cases.
Familiarity with cloud platforms and architectures (Azure preferred) and concepts including SaaS, PaaS, and IaaS.
Effective communication and leadership skills for guiding technical decisions, influencing stakeholders, and mentoring team members.
Business Experience:
Bachelor's degree or equivalent combination of education and experience required (Master's preferred).
Typically requires 7+ years of relevant professional experience in data engineering, analytics, or related fields.
Hands-on experience with advanced ETL/ELT development, SQL/Python scripting, and enterprise data integration across multiple platforms.
Experience with modern data ecosystems and large-scale data processing frameworks preferred.
Experience in healthcare or other regulated industries is strongly preferred.
Benefits
Health insurance
Additional Information
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.
Position Summary :
The Sr Data Specialist provides technical leadership in designing, implementing, and optimizing McKesson's enterprise data infrastructure to enable advanced analytics and decision-making. This position is responsible for building scalable data pipelines, developing ETL programs, and ensuring data integrity, reliability, and compliance within a regulated environment.
The role involves creating custom software components, maintaining metadata repositories, and implementing processes for data standardization and quality improvements. With an automation-first and enterprise-first mindset, the Sr Data Specialist collaborates with architects, analysts, data scientists, and governance teams to deliver scalable, reusable, and production-ready data solutions, including support for advanced analytics and AI-driven use cases that drive strategic and operational outcomes.
Mckesson · On, Mississauga, Canada