Sr. Associate Data Engineering

As a Sr. Associate Data Engineering at McKesson, you will be responsible for designing and implementing data processing pipelines, primarily using ETL techniques. This involves collaborating with cross-functional teams to transform business requirements into technical specifications, writing complex SQL queries, and maintaining data quality across different platforms, such as databases and data lakes.

To qualify for the Sr. Associate Data Engineering role at McKesson, candidates should have at least 2 years of experience with ETL tools, cloud data technologies, and programming in languages like Python. A bachelor’s degree in Computer Science or a related field is essential, along with a strong understanding of SQL and relational databases. Familiarity with machine learning concepts would be advantageous.

While prior experience in eCommerce is preferred for the Sr. Associate Data Engineering position at McKesson, it is not strictly required. Candidates who have worked in distribution, retail, or technology sectors may also qualify, provided they have relevant skills and a solid foundational understanding of data processing and analytics.

For a Sr. Associate Data Engineer role at McKesson, critical skills include proficiency in ETL tools, cloud data technologies (like Azure and GCP), strong SQL skills for complex queries, and programming experience in Python. Additionally, a strong work ethic and the ability to collaborate effectively with cross-functional teams are essential for success.

The work culture at McKesson for a Sr. Associate Data Engineering is inclusive and growth-oriented. The company promotes innovation and teamwork, allowing employees to thrive while making real impacts in healthcare. Employees are encouraged to share new ideas and are provided opportunities for personal and professional development.

When responding to this question, detail specific ETL tools you've worked with, such as Apache NiFi or Talend, and describe a project where you successfully designed and implemented an ETL pipeline, focusing on the results it achieved.

Be sure to highlight your approach to validating data at various stages of processing. Provide examples of checks or balances you implement and discuss any tools or scripts you've developed to ensure data integrity.

Share concrete examples of previous collaborations with teams from different domains, outlining how you translated technical requirements into actionable data tasks and how effective communication played a key role in project success.

Discuss the scalability, flexibility, and efficiency that cloud technologies provide for data processing, especially in handling large volumes of data. Mention your experience with cloud services like Azure or GCP and how they can enhance analytical capabilities.

Detail specific data visualization tools you've used, such as Tableau or Power BI. Explain how these tools have enabled you to present data insights effectively to stakeholders and how that influenced decision-making.

Summarize your SQL knowledge and provide a brief overview of a complex query you've constructed, detailing the purpose behind it, the data it interacted with, and the insights that resulted from it.

Discuss any methodologies like Agile or Scrum that you've implemented in your projects. Highlight how these frameworks helped in managing tasks efficiently and produced timely results.

Provide examples of how you've approached unstructured data, the tools used for analysis, and the techniques you implemented to transform it into a structured format for meaningful insights.

Share a specific project that posed difficulties, whether it was technical hurdles or time constraints. Explain how you analyzed the situation, adapted your approach, and the successful outcome that ensued.

Express your enthusiasm for McKesson's mission and how the role aligns with your passion for transforming healthcare through data engineering. Mention specific aspects of the company that excite you, such as its culture or innovative projects.