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 Senior Data Engineer you will be working on developing and maintaining data pipelines that extract, transform, and load (ETL) data from various sources into a centralized data storage system, such as a data warehouse or data lake. Ensure the smooth flow of data from source systems to destination systems while adhering to data quality and integrity standards. In addition to having impact on a great team, you’ll also discover the career opportunities you’d expect from an Industry Leader.
Schedule: Full-time position with standard working hours of Monday – Friday, standard business hours.
Careers with Optum offer flexible work arrangements and individuals who live and work in the Republic of Ireland will have the opportunity to split their monthly work hours between our Dublin or Letterkenny office and telecommuting from a home-based office in a hybrid work model.

REQUIRED QUALIFICATIONS:

• Extensive experience designing data solutions including data modeling (Knowledge on Data Vault is a plus)
• Well versed in Python(Programming, packaging, unit-testing), in fulfilling multiple general-purpose use-cases, and not limited to developing data APIs and pipelines
• Experience with Apache Spark and related Big Data stack and technologies
• Hands-on experience developing data processing jobs (PySpark / SQL) that demonstrate a strong understanding of software engineering principles
• Experience orchestrating data pipelines using technologies like ADF, Airflow, etc
• Experience working with batch data, knowing the strengths and weaknesses
• Experience building data pipelines on Azure/ Databricks, following best practices in Cloud deployments
• Knowledge of working with Hadoop ecosystem
• Fluent in SQL (any flavor), with experience using Window functions and more advanced features
• Understanding of DevOps tools, Git workflow and building CI/CD pipelines
• Ability to work with business and technical audiences on business requirement meetings, technical white boarding exercises, and SQL coding/debugging sessions
• Experience supporting big data pipelines and optimizing them
• Experience applying data governance controls within a highly regulated environment

PREFERRED QUALIFICATIONS:

• Bachelor’s Degree (or higher) in Database Management, Information Technology, Computer Science or similar
• Proven Data Engineering experience
• Experience working in projects with agile/scrum methodologies.
• Data modelling skills - Understanding of Medallion Architecture and Data-Vault2
• Familiar with Azure Databricks and/or Snowflake
• Experience working with real-time, knowing the strengths and weaknesses.
• Experience with shell scripting
• Familiarity with production quality ML and/or AI model development and deployment
• Familiarity with de-identification/masking of data

• Data Pipeline Development: Develop and maintain data pipelines that extract, transform, and load (ETL) data from various sources into a centralized data storage system, such as a data warehouse or data lake. Ensure the smooth flow of data from source systems to destination systems while adhering to data quality and integrity standards
• Data Integration: Integrate data from multiple sources and systems, including databases, APIs, log files, streaming platforms, and external data providers. Handle data ingestion, transformation, and consolidation to create a unified and reliable data foundation for analysis and reporting
• Data Transformation and Processing: Develop data transformation routines to clean, normalize, and aggregate data. Apply data processing techniques to handle complex data structures, handle missing or inconsistent data, and prepare the data for analysis, reporting, or machine learning tasks
• Contribute to common frameworks and best practices in code development, deployment, and automation/orchestration of data pipelines
• Implement data governance in line with company standards
• Partner with Data Analytics, Data Science and Product leaders to design best practices and standards for developing and productionalizing data pipelines
• Partner with Infrastructure leaders on architecture approaches to advance the data and analytics platform, including exploring new tools and techniques that leverage the cloud environment (Azure, Snowflake, others)
• Monitoring and Support: Monitor data pipelines and data systems to detect and resolve issues promptly. Develop monitoring tools, alerts, and automated error handling mechanisms to ensure data integrity and system reliability
  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.