Lead Data Engineer

McKesson•Mississauga, ON

About The Position

The PSaS Decision Intelligence (DI) Data Architecture & Engineering team is seeking a technically strong and operationally focused Lead Data Engineer to own the day‑to‑day operations of our enterprise Data & Analytics platforms. This role is centered on KTLO (Keep the Lights On) ownership—ensuring platform stability, SLA‑driven support, service request fulfillment, and continuous improvement across both modern and legacy data ecosystems. The role combines deep technical expertise with operational leadership and close partnership with data, analytics, and business stakeholders.

Requirements

Proven depth of experience delivering and supporting enterprise‑scale data engineering solutions in production environments
Extensive hands‑on expertise with Databricks, Snowflake, Azure Data Factory, PySpark, analytical SQL, and modern cloud data platforms
Strong experience with data visualization and analytics consumption tools such as Power BI
Working knowledge of SAP ecosystems and legacy technologies including SQL Server, IBM DataStage, and Unix scripting
Demonstrated ownership of production platforms and KTLO operations in SLA‑driven environments
Strong understanding of data architecture, data modeling, data governance, metadata, and lineage
Experience analyzing and modeling structured data using statistical, mathematical, or data‑mining techniques
Familiarity with enterprise infrastructure concepts including SaaS, PaaS, IaaS, and Infrastructure as Code (IaC) approaches
Strong troubleshooting, monitoring, and performance‑tuning skills across data platforms and analytical services
Ability to influence architecture and technical direction without formal people management responsibility
Excellent communication and stakeholder management skills, with the ability to explain complex concepts clearly
Demonstrated ability to independently drive outcomes while operating under consultative direction
Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Master’s or Doctorate qualifications.

Nice To Haves

Experience supporting Decision Intelligence, Distribution, or PSaS business domains
Exposure to Splunk, Alation, or data observability and cataloging tools
Experience operating in highly regulated, complex enterprise environments
Strong documentation, data stewardship, and operational excellence mindset

Responsibilities

Lead day‑to‑day operations of PSaS Data & Analytics platforms, ensuring platform reliability, performance, and SLA compliance
Own KTLO responsibilities including incident management, root cause analysis, service request execution, and minor enhancements
Partner with Data Engineers, Data Scientists, Architects, and Program Managers to design, support, and maintain enterprise data solutions
Support data exploration and analysis activities, including requirements assessment, data source identification, and exploratory research
Define, maintain, and govern data definitions, business rules, metadata, and lineage
Ensure high data quality through validation, monitoring, and testing (functional, regression, exploratory)
Identify, document, and advocate for reduction of technical debt across the data landscape
Design scalable, reusable, automation‑first data engineering solutions with an enterprise mindset
Build and support batch and real‑time data pipelines across internal and external data sources
Collaborate across Agile teams to design, develop, test, implement, and support end‑to‑end data solutions
Implement data governance practices in partnership with business stakeholders and enterprise data governance teams
Troubleshoot, monitor, and performance‑tune data platforms, pipelines, and analytical services
Communicate platform health, insights, and outcomes through documentation, reports, and presentations
Coordinate delivery across internal teams, external partners, and multi‑shore resources