Data Engineer

$105,200 - $175,300/Yr

McKesson - Irving, TX

Full-time - Mid Level

Irving, TX

1-10 employees

Merchant Wholesalers, Nondurable Goods

About the position

As a Data Engineer at Ontada, a part of McKesson, you will play a crucial role in transforming healthcare through technology. Your contributions will significantly impact the development of our analytic platform, which is designed to convert clinical, financial, and operational data into actionable insights. This platform is essential for enabling population health management and performance optimization in oncology practices. You will be part of a team that is dedicated to improving the fight against cancer by providing evidence-based, personalized care and supporting biopharma companies in drug development. Your work will influence every stage of the treatment journey, from patient care to clinical trials and commercial launches of new therapies. In this position, you will advocate for new technologies and participate in architectural decisions that shape the future of our data solutions. You will engage in the full product development lifecycle, which includes defining, designing, implementing, and testing data solutions. Your responsibilities will include designing, developing, and maintaining scalable data pipelines and architectures, as well as implementing solutions using Azure Cloud services such as Azure Data Lake and Azure SQL Database. You will utilize Databricks for data processing and analytics, and leverage Big Data technologies like Spark to manage large volumes of both structured and unstructured data. Ensuring data quality, integrity, and security will be paramount in your role. You will implement best practices for data governance and collaborate with data scientists and analysts to meet business needs. Additionally, you will optimize data systems for performance and scalability, document workflows and architectures, and develop tools to maintain system availability and monitor data quality. Your understanding of HIPAA standards will guide your work, and you will be expected to cross-train team members in your areas of expertise. This position requires authorization to work in the U.S., and unfortunately, no sponsorship or relocation assistance is available.

Responsibilities

• Advocate for new technologies and participate in architecture decisions.
• Participate in the full lifecycle of product development, from definition, design, implementation, and testing.
• Design, develop, and maintain scalable data pipelines and architectures.
• Implement data solutions using Azure Cloud services, including Azure Data Lake and Azure SQL Database.
• Utilize Databricks for data processing, transformation, and analytics.
• Leverage Big Data technologies (e.g., Spark) to manage and process large volumes of structured and unstructured data.
• Ensure data quality, integrity, and security across all data pipelines and storage solutions.
• Implement data quality and governance best practices to ensure data accuracy and integrity.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs.
• Optimize data systems and pipelines for performance and scalability.
• Document data workflows, processes, and architecture for future reference.
• Develop tools and utilities to maintain high system availability, monitor data quality, and provide statistics.
• Understand and apply HIPAA standards and regulations to all areas of work.
• Cross-train team members on areas of technical expertise.

Requirements

• Degree or equivalent and typically requires 4+ years of relevant experience.
• BS or MS in Computer Science, Mathematics or related field.
• 4+ years of professional experience with architecting and developing cloud solutions in Azure.
• 4+ years of programming experience in SQL and Python for data processing.
• 3+ years of experience working in big data technologies such as Spark or Hadoop.
• Knowledge of data modeling for both data warehousing and Big Data.
• Experience with machine learning and data analytics.
• Familiarity with CI/CD pipelines and DevOps practices.
• Expertise in data structures, algorithms, and complexity analysis.
• Experience in engineering large-scale distributed systems in a production environment.
• Develop Python, PySpark, Spark scripts to filter/cleanse/map/aggregate data.
• Working knowledge of SQL or other relational databases, and data warehousing principles.
• Strong verbal and written communication skills, including the ability to articulate complex technical concepts to non-technical stakeholders.
• Ability to work gracefully and effectively in high-pressure situations.
• Knowledge of healthcare IT systems and workflows.

Nice-to-haves

• Experience with Visualization tools like Tableau or PowerBI.

Benefits

• Competitive compensation package including base pay and potential bonuses.
• Annual bonus or long-term incentive opportunities based on performance, experience, and skills.
• Comprehensive health insurance coverage.
• Retirement savings plan options.
• Support for professional development and career growth opportunities.