Lead Data Engineer

McKesson•Mississauga, ON

1d•$122,100 - $162,800•Hybrid

About The Position

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. Our PSaS Decision Intelligence (DI) Data Architecture and Engineering team is seeking a technically adept and operationally focused operations lead engineer for managing the day-to-day operations of our PSaS Data & Analytics platforms. This role is centered on KTLO (Keep the Lights On) responsibilities, ensuring SLA-driven support, service request fulfillment, and minor enhancements. The ideal candidate will have expertise in Databricks, Snowflake, Power BI, SAP, and legacy technologies such as SQL Server, DataStage, and Unix scripting, with a strong understanding of distribution business. The Lead Data Engineer will be part of McKesson Decision Intelligence team, and responsibilities include managing data exploration and analysis, requirements assessment, data source identification, exploratory research, and defining as well as maintaining data definitions, business rules, and lineage. Additional duties involve documentation, collaborating with Data Architects and Engineers on product design, data stewardship, metadata management, ensuring data quality, conducting different types of testing (functional, regression, exploratory), and preparing and executing test cases and plans.

Requirements

Bachelor's or master's degree in data science, Statistics, Computer Science, Economics, or a related field.
7+ years of experience in data analytics, with at least 2 years in a leadership or mentorship role.
Proficiency in SQL, Python, R, or similar analytical tools.
Experience with data visualization platforms such as Power BI, Tableau, or Looker.
Strong understanding of statistical analysis, predictive modeling, and data mining techniques.
Experience with analytical tools such as Databricks & Snowflake
Excellent communication and stakeholder management skills.
Ability to manage multiple projects and priorities in a fast-paced environment.
Leadership Skills: Exceptional ability to lead, mentor, and inspire teams, fostering an environment of accountability and innovation. This position operates under consultative direction towards broad corporate goals, requiring a high degree of initiative and independence in achieving project outcomes.
Strategic Thinking: Strong analytical skills and the ability to develop strategies that align with long-term objectives.
Problem Solving: Innovative and creative problem-solving skills capable of handling complex challenges.
Expertise in Databricks, Snowflake, Power BI, SAP, and legacy technologies such as SQL Server, DataStage, and Unix scripting, with a strong understanding of distribution business.
Must be well versed in general infrastructure technology and understand public and private cloud concepts such as Software as a Service (SaaS), Platform as a Service (PaaS), Desktop as a Service (DaaS), and Infrastructure as a Service (IaaS)

Nice To Haves

Experience with SAP and IBM DataStage is also extremely beneficial.

Responsibilities

Support a cross-functional team and provide in-depth data insights for complex business problems that can be approached with advanced analytics
Work closely with the other Data Engineers and Scientists to deliver results
Citizen of PSAS BU data engineering team and enable the BU Driven Data Insights
Coordinate and collaborate with program managers and other internal stakeholders including gathering requirements and modeling criteria
Leverage tools and resources to plan, evaluate and execute strategic initiatives
Strong delegation and management skills to ensure work is conducted in a timely, quality fashion by internal and external partners and multi-shore teams/resources.
Continuously improve and optimize business processes and operations. Identifying, publicizing the tech debt across data landscape and championing addressal pursuits.
Data Engineering and Analytics support
Thinks in automation first, enterprise first and reusability mindset. Develops solution architectures and designs and helps build consensus among teams to champion the data solutions.
Collaborates with and across Agile teams to design, develop, test, implement, and support technical solutions with full stack of Data technologies, tools and processes.
Implements data governance practices in partnership with business stakeholders and peers, data governance office teams and solution teams to advocate for data literacy and data democratization across enterprise.
Builds scalable and reliable data engineering solutions for moving data efficiently across systems from various internal and external data sources in the batch and real-time mode
Analyzes, models structured data and implement/scale algorithms to support analysis using advanced statistical and mathematical methods from statistics, data mining, econometrics, and operations research, using distributed and parallel programming techniques.
Experience with automation to Infrastructure (IaC - Infrastructure as Code)
Troubleshooting, Monitoring and Performance Tuning of various software components of various data science analytical solutions, RESTful web services etc...
Understanding of large database mining tools and statistical languages utilized to efficiently build approaches and execute on analytical use cases. Specific experience with Snowflake, Databricks, Azure data factory, PySpark, Analytical SQL, Splunk, Alation, R, Python. Experience with SAP and IBM DataStage is also extremely beneficial.
Communicate results and educate others through reports and presentations.