Lead Data Platform Engineer 1

You will serve as a trusted technical leader responsible for enterprise-scale data architecture, cloud platform strategy, governance, security, and operational excellence. Working closely with architects, product teams, security partners, and business stakeholders, you will influence strategic technology decisions while mentoring engineers and advancing engineering best practices.

What You'll Do:

• Define technical strategy and architecture standards for enterprise data platforms and engineering solutions.
• Lead the design, implementation, and optimization of scalable cloud-based data platforms supporting analytics, AI, machine learning, and reporting workloads.
• Drive large-scale modernization, migration, and platform transformation initiatives.
• Establish best practices for DataOps, DevOps, CI/CD, Infrastructure as Code, and platform automation.
• Strengthen governance, security, compliance, access management, and data protection controls within regulated environments.
• Partner with architecture, security, product, and engineering leadership to influence platform roadmaps and technology decisions.
• Lead incident response, platform reliability, monitoring, observability, and operational excellence initiatives.
• Mentor engineers and foster a culture of innovation, technical excellence, and continuous improvement.

Basic Requirements:

• 10+ years of professional experience in Data Engineering, Data Platform Engineering, Cloud Engineering, or related disciplines.
• Bachelor's degree in Computer Science, Engineering, Information Technology, or related field (or equivalent combination of education and experience).
• Experience designing and implementing enterprise-scale data architecture, ETL/ELT pipelines, and modern data platforms.
• Advanced proficiency with SQL and Python for large-scale data processing and performance optimization.
• Hands-on experience with Azure Databricks administration, Snowflake, Azure Data Lake Storage, and Azure Data Factory.
• Experience implementing cloud security, governance, identity and access management, and compliance controls.
• Proven ability to lead complex technical initiatives and influence architectural decisions across multiple teams.
• Strong communication and stakeholder management skills with the ability to translate technical concepts for diverse audiences.

Preferred Skills/Experience:

· Understanding of Agile software development methodologies, including Scrum and Kanban.

· Experience designing and implementing cloud-based data, analytics, AI, and machine learning platforms with strong focus on availability, performance, resiliency, security, scalability, observability, and cost optimization.

· Experience developing reference architectures, reusable patterns, platform guardrails, and engineering standards across Azure, Databricks, Kubernetes, networking, storage, identity, secrets management, and data services.

· Experience evaluating platform requirements and making architectural trade-offs across reliability, security, compliance, interoperability, operational efficiency, vendor dependency, and total cost of ownership.

· Experience establishing secure integration patterns for AI applications, agents, enterprise data, vector search, private connectivity, content controls, approved model providers, and secrets management.

· Experience implementing observability and operational excellence using OpenTelemetry, Prometheus, Grafana, cloud monitoring, centralized logging, and service-level reporting.

· Experience building and maintaining Infrastructure-as-Code, configuration automation, and CI/CD or GitOps workflows for repeatable platform provisioning, deployment, testing, and lifecycle management.

· Experience applying security-by-design, zero-trust, least-privilege, and defense-in-depth principles across identity, access management, networking, encryption, data protection, platform administration, and AI services.

· Experience working with large-scale batch and real-time data platforms, distributed systems, streaming technologies, data warehouses, and databases, including Databricks, Snowflake, Kafka, Oracle, SQL Server, PostgreSQL, and MongoDB.

· Experience managing enterprise data platforms and governance capabilities, including data storage, processing, security, quality, lineage, and communicating technical, financial, and operational considerations to business and engineering leaders.

· Azure Administrator Certification preferred.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$122,100 - $162,800

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McKesson provides equal employment opportunities to 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. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

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