Senior / Lead Data Engineer

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Quick Summary

Key Responsibilities

Senior/Lead Data Engineer Current Need: The Senior / Lead Data Engineer will be part of McKesson Decision Intelligence team, and responsibilities include managing data exploration and analysis,

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Data EngineerData

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.

The Senior / 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.

Responsibilities

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Support a cross-functional team and provide in-depth data insights for complex business problems that can be approached with advanced analytics

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Work closely with the other Data Engineers and Scientists to deliver results

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Citizen of PSAS BU data engineering team and enable the BU Driven Data Insights

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Coordinate and collaborate with program managers and other internal stakeholders including gathering requirements and modeling criteria

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Leverage tools and resources to plan, evaluate and execute strategic initiatives

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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.

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Continuously improve and optimize business processes and operations. Identifying, publicizing the tech debt across data landscape and championing addressal pursuits.

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Data Engineering and Analytics support

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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.

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Collaborates with and across Agile teams to design, develop, test, implement, and support technical solutions with full stack of Data technologies, tools and processes.

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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.

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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

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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.

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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) Experience with automation to Infrastructure (IaC - Infrastructure as Code)

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Troubleshooting, Monitoring and Performance Tuning of various software components of various data science analytical solutions, RESTful web services etc...

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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.

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Communicate results and educate others through reports and presentations.

Requirements

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McKesson provides equal employment opportunities to applicants and employees and is committed to a diverse and inclusive environment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age or genetic information. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.