As a Data Engineer, you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross product and feature teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software engineers, data analysts, BI engineers and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.

 

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using cloud-native and big data principles.
• Build the framework to enable analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Product, Data and Marketing teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and regions.
• Create data processes and tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

Nice to Have:

• Advanced working knowledge and experience working with relational databases, query authoring as well as working familiarity with a variety of databases.
• Experience building and optimizing big data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Experience with message queuing, stream processing, and highly scalable big data stores.
• Experience with end-to-end API design, implementation and sustainment.
• Strong analytic skills related to working with unstructured and structured datasets.
• Project management and organizational skills to self-scope and direct on a day-to-day basis.
• Experience supporting and working with cross-product/feature teams in a dynamic environment.
• The ideal candidate should also have experience using the following software/tools:
  
  • Experience with big data tools: Hadoop, Spark, Kafka, Beam, etc.
  • Experience with both relational SQL and NoSQL databases, including Postgres, MongoDB, etc.
  • Experience with data pipeline and workflow management tools such as Apache Airflow, etc.
  • Strong Experience with Code Management + DevOps: Github, Github Actions, Concourse CI, Terraform, Atlantis, etc.
  • Experience with Google Cloud Platform (GCP) cloud services: BigQuery, DataFlow, PubSub, CloudSQL, Cloud Storage, Cloud Composer, VertexAI
  • Knowledge of the FHIR standard and/or healthcare data
  • Experience with object-oriented/object function scripting languages: Python, Go, Scala, Java, C++, etc.