Data Engineer
Indexed description
Our teams are at the forefront of building and adapting the latest technologies to propel healthcare forward in a way that better serves everyone. With our hands at work across all aspects of health, we use the most advanced development tools, AI, data science and innovative approaches to make the healthcare system work better for everyone.
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.
What You Will Do
- Design, build and implement automation processes for production release of data engineering, machine learning and business intelligence processes
- Write code, and leverage tools, to transform data to incorporate business logic as defined in conjunction with the Optum business and technology partners
- Design, code, test, document, and maintain high-quality and scalable Big Data solutions
- Analyze raw data sources, data transformation, structural requirements for new software and application
- Migrate data from legacy systems to new solutions
- Design conceptional and logical data model and flowcharts
- Define security and backup strategy for data solutions
- Design, build and implement real time / near real time data pipelines
- Design and prototype data monitoring models for pipeline
- Write technical documentation
What You Will Bring
- Proven extensive experience in Data Engineering
- Proven experience working with data processing technologies and SQL database platforms
- Demonstrated advanced SQL proficiency
- Proven experience working with relational and non-relational database technologies
- Proven experience implementing ETL solutions and applying data warehousing, data modeling, and architectural principles within large-scale environments
- Demonstrated working knowledge of public cloud platforms, including Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP), and developing applications within Linux environments
- Proven experience working with Hadoop, Snowflake, Vertica, Redshift, Synapse, or similar data platforms
- Proven experience utilizing Spark and Databricks to support data processing and machine learning workloads
- Proven experience implementing data pipeline orchestration solutions using Apache Airflow, including Airflow operators and hooks
- Proven experience designing, implementing, and supporting data applications using Kubernetes and Docker
- Proven hands-on experience with Python, with demonstrated experience using Java, Scala, or similar programming languages
- Proven experience working within Agile and Scrum delivery environments
- Proven experience developing solutions hosted on major cloud platforms, including Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP)
- Proven experience building OLAP cubes and analytical databases
- Proven experience working within data warehouse environments
- Proven experience working with Apache Kafka
- Demonstrated knowledge of DevOps tools and practices
- Demonstrated knowledge of Agile development methodologies
- Demonstrated knowledge of Kimball and Data Vault data modeling methodologies
- Proven experience working with dbt (Data Build Tool)
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