Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together.
As a Fortune 5 business, we’re one of the world’s leading healthcare companies. There are no limits here on the resources you’ll have or the challenges you’ll encounter.
We have been supporting global healthcare systems from Ireland and the UK for more than 20 years, building a dynamic and diverse team of more than 2,100 talented individuals. With a continued record of growth and stability, we’re on the constant lookout for fresh talent to join our expanding team’s healthcare system work better for everyone.
As a Principal Data Engineer, this individual will be a key member of the business team, responsible for overseeing the data engineering of MVP/prototype data products and infrastructure. You will support Optum Rx Strategy team, ensuring efficient data pipelines, automating monitoring of data QA, and collaborating with the Data Strategy team on migration efforts. This role requires a blend of technical skills in data engineering and ETL pipelines, along with the ability to drive strategic initiatives within the business team.

Primary Roles & Responsibilities:

• Oversee data engineering of MVP/prototype data products and infrastructure to support MAC Strategy & Benchmarking objectives
• Design, implement, configure, and maintain data ingestion and integration processes
• Create and maintain optimal data pipeline architecture
• Automate monitoring and ensure efficient data QA processes
• Collaborate with the Data Strategy team on data migration efforts
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and re-designing infrastructure for scalability and cost reduction
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies
• Support the testing and auditing team members to ensure quality checks involved in reporting of sensitive data
• Ensure data is maintained and secured, adhering to the ‘least-privilege’ security principle for team access
• Work collaboratively with management, clients, and stakeholders to assist with data-related technical issues and support their data reporting needs
• Analyze existing operations and schedule training sessions and meetings to discuss improvements
• Keep up-to-date with industry trends and developments in data engineering and related fields

You will be rewarded and recognised for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role, as well as providing development for other roles you may be interested in.

REQUIRED QUALIFICATIONS:

• Master’s Degree (or higher) in a heavily technical discipline (e.g. data science, computer science)
• Hands-on experience with data engineering, data architecture, and ETL pipeline development
• Experience programming in a back-end language (e.g., Spark, Java, J2EE, Kafka)
• Advanced working SQL and No-SQL knowledge and experience with various databases (e.g., MySQL, NoSQL, Hadoop, MongoDB)
• Experience with IT methodologies: e.g., ITIL, Agile, DevOps, SDLC

PREFERRED QUALIFICATIONS:

• Experience using Python data science/engineering libraries
• Public cloud experience, especially with Microsoft Azure
• Experience with version control tools e.g. Git and Github
• Experience working in global health insurance payer organizations, focusing on data stewardship, data integration, business intelligence/analytics, data warehousing, and IT service management
• Experience with machine learning (ML), artificial intelligence (AI), and natural language processing (NLP) architecture and system administration
• DEVOPS engineering experience
• Human-centered design experience or exposure

• Oversee data engineering of MVP/prototype data products and infrastructure to support MAC Strategy & Benchmarking objectives
• Design, implement, configure, and maintain data ingestion and integration processes
• Create and maintain optimal data pipeline architecture
• Automate monitoring and ensure efficient data QA processes
• Collaborate with the Data Strategy team on data migration efforts
• Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and re-designing infrastructure for scalability and cost reduction
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and big data technologies
• Support the testing and auditing team members to ensure quality checks involved in reporting of sensitive data
• Ensure data is maintained and secured, adhering to the ‘least-privilege’ security principle for team access
• Work collaboratively with management, clients, and stakeholders to assist with data-related technical issues and support their data reporting needs
• Analyze existing operations and schedule training sessions and meetings to discuss improvements
• Keep up-to-date with industry trends and developments in data engineering and related field