Description:
The Sr Data Specialist provides technical leadership in designing, implementing, and optimizing McKesson’s enterprise data infrastructure to enable advanced analytics and decision-making. This position is responsible for building scalable data pipelines, developing ETL programs, and ensuring data integrity, reliability, and compliance within a regulated environment.
The role involves creating custom software components, maintaining metadata repositories, and implementing processes for data standardization and quality improvements. With an automation-first and enterprise-first mindset, the Sr Data Specialist collaborates with architects, analysts, data scientists, and governance teams to deliver scalable, reusable, and production-ready data solutions, including support for advanced analytics and AI-driven use cases that drive strategic and operational outcomes.
Key Responsibilities:
- Design and implement scalable data pipelines and ETL/ELT programs to integrate complex data sources across internal and external systems, supporting both batch and real-time processing.
- Write and optimize advanced queries using SQL and Python to improve data processing, performance, and analytical outcomes.
- Lead data exploration, requirements analysis, and data source identification for analytical and operational use cases.
- Develop and maintain metadata repositories, including data definitions, lineage, and business rules, ensuring data integrity and usability across enterprise systems.
- Create and implement processes for data standardization, reliability, quality improvement, and governance compliance.
- Troubleshoot and resolve complex data analytic issues across production and development environments, including database and pipeline performance tuning.
- Develop and maintain reusable query libraries and custom software components to support analytics, reporting, and AI/ML solutions.
- Recommend and implement modern tools, technologies, and best practices to enhance data engineering capabilities and platform performance.
- Ensure adherence to governance, security, and regulatory compliance through rigorous data quality checks, validation processes, and documentation.
- Support testing, monitoring, and validation of data pipelines, including development of test cases and quality checks.
- Collaborate with cross-functional teams to align data solutions with enterprise architecture, governance standards, and business priorities.
- Provide technical leadership, influence design decisions, and mentor junior engineering teams to promote best practices and continuous improvement.
Minimum Job Qualifications (Knowledge, Skills, & Abilities):
- Expertise in designing and maintaining scalable data pipelines, ETL/ELT processes, and data integration across complex enterprise systems.
- Advanced proficiency in SQL and Python for data processing, query optimization, and analytics enablement (R is a plus).
- Strong knowledge of data modeling, data architecture, metadata management, and data governance practices.
- Hands-on experience with modern data platforms and tools such as Databricks, Snowflake, Azure Data Factory, and PySpark.
- Familiarity with big data and distributed technologies such as Hadoop, Kafka, and distributed file systems.
- Ability to implement processes for data standardization, reliability, quality improvement, and stewardship.
- Competence in troubleshooting complex data issues, resolving data model conflicts, and optimizing performance.
- Experience developing custom components, analytics applications, and enabling advanced analytics/AI use cases.
- Familiarity with cloud platforms and architectures (Azure preferred) and concepts including SaaS, PaaS, and IaaS.
- Effective communication and leadership skills for guiding technical decisions, influencing stakeholders, and mentoring team members.
Business Experience:
- Bachelor’s degree or equivalent combination of education and experience required (Master’s preferred).
- Typically requires 7+ years of relevant professional experience in data engineering, analytics, or related fields.
- Hands-on experience with advanced ETL/ELT development, SQL/Python scripting, and enterprise data integration across multiple platforms.
- Experience with modern data ecosystems and large-scale data processing frameworks preferred.
- Experience in healthcare or other regulated industries is strongly preferred.
Working Conditions:
- In office requirement, we are Flex and Connect with 2 days a week in office