Senior Data Engineer, Transcarent

• You are entrepreneurial and mission-driven and can present your ideas with clarity and confidence
• You are a high-agency person. You refuse to accept undue constraints and the status quo and will not rest until you figure things out
• Advanced expertise in python and dbt for data pipelines
• Advanced working SQL knowledge and experience working with relational databases
• Experience building and optimizing big data pipelines, architectures, and data sets. A definite plus with healthcare experience
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Strong analytic skills related to working with unstructured datasets
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• A successful history of manipulating, processing, and extracting value from large disconnected datasets
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores
• Strong project management and organizational skills
• Experience supporting and working with cross-functional teams in a dynamic environment
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field
• Good to have healthcare domain experience

Desirable

• We are looking for data engineers excited to create a single source of truth that will power the decisions for the company for other developers, products, clinical teams, data analysts, data scientists, member experience, and more
• They will need to be able to ingest various sorts of application and health data, leverage our Snowflake data warehouse to load it, and transform the data into various data sets to offer it self-serve in a secure, compliant manner
• 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
• Be a data champion and seek to empower others to leverage the data to its full potential
• Create and maintain optimal data pipeline architecture with high observability and robust operational characteristics
• 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 data extraction, transformation, and loading using SQL, python, and dbt from various sources
• Work with stakeholders, including the Executive, Product, Clinical, Data, and Design teams, to assist with data-related technical issues and support their data infrastructure needs
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader

Total funding: $424m

More than 60% of US workers who receive health insurance are enrolled into an employer-funded/managed self-insured plan. While such plans can reduce premiums for employers, this typically comes at the cost of quality and increased friction, as opposed to self-insuring through a traditional insurance company.