Specialist, Data Engineer

McKesson•Irving, TX

21d

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. Job Title Specialist, Data Engineer Summary The Specialist, Data Engineer is a fully competent individual contributor within McKesson’s Decision Intelligence organization, responsible for designing, building, and maintaining scalable data pipelines and analytics solutions. This role operates independently with limited direction and partners closely with cross‑functional teams to deliver reliable, high‑quality data products that enable business insights.

Requirements

Strong hands‑on experience building and supporting data pipelines in enterprise environments.
Ability to work independently on complex tasks with minimal supervision.
Solid understanding of data modeling, ETL/ELT patterns, and analytics enablement.
Experience partnering with technical and business stakeholders to deliver data solutions.
Technical Skills Proficiency in SQL and Python .
Hands‑on experience with modern data platforms and tools such as: Databricks, Snowflake, Azure Data Factory PySpark, analytical SQL Power BI and/or Tableau Apache Airflow and/or dbt
Experience working with structured and semi‑structured data.
Familiarity with cloud platforms (Azure preferred).
Understanding of data quality, testing, and performance optimization concepts.
Minimum Requirements Degree or equivalent and typically requires 4+ years of relevant experience.

Nice To Haves

Experience supporting advanced analytics or data science workloads.
Exposure to real‑time or event‑driven data pipelines (Kafka / Event Hub).
Familiarity with data governance, metadata, or lineage tools.
Experience in large, matrixed enterprise environments

Responsibilities

Design, build, and maintain batch and near‑real‑time data pipelines supporting analytics and reporting use cases.
Translate business and analytical requirements into technical data engineering solutions.
Develop, optimize, and maintain data transformations, models, and datasets for downstream consumption.
Write and maintain complex SQL queries and Python‑based data processing logic.
Collaborate with Data Architects, Product Managers, Analysts, and Data Scientists to support analytics and ML initiatives.
Ensure data quality, reliability, and performance across data pipelines and platforms.
Implement testing, monitoring, and basic observability for data workflows.
Troubleshoot data issues and support production data pipelines as needed.
Contribute to documentation, standards, and best practices within the data engineering team.
Follow enterprise data, security, and governance standards in all solutions.