Graph Data Engineer

Olive’s AI workforce is built to fix our broken healthcare system by addressing healthcare’s most burdensome issues -- delivering hospitals and health systems increased revenue, reduced costs, and increased capacity. People feel lost in the system today and healthcare employees are essentially working in the dark due to outdated technology that creates a lack of shared knowledge and siloed data. Olive is designed to drive connections, shining a new light on the broken healthcare processes that stand between providers and patient care. She uses AI to reveal life-changing insights that make healthcare more efficient, affordable and effective. Olive’s vision is to unleash a trillion dollars of hidden potential within healthcare by connecting its disconnected systems. Olive is improving healthcare operations today, so everyone can benefit from a healthier industry tomorrow.

Olive is searching for experienced engineers to provide technical leadership and guidance as we build our technology platform. Data Engineers within Olive Graph work with the Olive Product Management team to deliver value in our Olive Graph . We encourage a growth mindset amongst all of our engineers and value those with the drive to be continuously expanding industry knowledge. A successful Data Engineer will possess strong analytical as well as technical skills, and have the ability to communicate the logic behind technical decisions to non-technical stakeholders.

Responsibilities (to include but not limited to):

• Create data transformation pipelines with Airflow, Gitlab, and various graph data toolkits to convert numerous, heterogeneous data sources into entries in the Olive Knowledge Graph
• Work alongside the Ontology Engineers, Platform Engineers, and Product to ensure high quality data
• Analyze data pipelines and make the necessary changes to optimize performance.
• Diagnose and resolve issues promptly and in accordance with maintainability goals.
• Work with a variety of technical and non-technical people.
• Embrace changing requirements.
• Create and maintain efficient, reliable infrastructure with code
• Drive automation using popular cloud orchestration, configuration management, and CI/CD system
• Design and implement:
  • Solutions to consume from sources like data lakes, RDBMS, and NoSQL data layers
  • Data quality check frameworks
  • Alerting and monitoring for overall data stack
  • Scalable data pipelines
• Work with languages such as: SQL, SPARQL, Python, Java, Bash

Requirements

• Bachelor’s in Computer Science, Mathematics, Statistics, Physics or relevant equivalent experience
• 5+ years of Data Engineering or data warehousing experience
• A strong understanding of operating systems, networking, and software engineering fundamentals
• Experience using AWS or other virtualized infrastructure
• Experience managing a container-based microservice architecture, including orchestration, service-discovery, monitoring, and debugging
• Proficient in a scripting language (e.g. Bash, Python, Ruby, Perl, PowerShell, etc.)
• Experience orchestrating infrastructure using CloudFormation, Terraform, or other similar tooling.
• Experience building in Linux and Windows systems (e.g. AWS Linux 2, Ubuntu, CentOS, ContainerLinux, etc.)
• Strong experience with SQL and No-SQL databases (e.g. MySQL, PostgreSQL, Oracle, MongoDB, SQL Server)

Ideal Experience:

• Experience with Big data solutions like Spark/Hadoop/Hive
• Experience with streaming infrastructure like Kafka, Kinesis or Apache Beam
• Experience with Data Lakes (Lake Formation/Snowflake) and Lake querying technologies (e.g. Athena, Redshift)
• Deploying or managing infrastructure across AWS AZs and regions.
• Experience with semantic web technologies (e.g. RDF, SPARQL, OWL)
• Knowledge of RDF engines such as Apache Jena Fuseki, Stardog, or AWS Neptune