Senior Data Engineer
Posted on 7/19/2023
INACTIVE
Comprehensive health & care platform
Company Overview
Trascarent’s mission is to create a new, different, and better health and care experience that puts health consumers in charge, directly connecting them with high-quality care, transparent information, and trusted guidance on their terms – measurably improving member experience, increasing health outcomes, and reducing costs.
Consumer Software
Company Stage
Series C
Total Funding
$298M
Founded
2020
Headquarters
San Francisco, California
Growth & Insights
Headcount
6 month growth
↑ 0%1 year growth
↓ -1%2 year growth
↑ 28%Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Redshift
Python
Airflow
NoSQL
Data Structures & Algorithms
Apache Spark
SQL
Apache Kafka
Java
AWS
Go
REST APIs
C/C++
Data Analysis
Snowflake
CategoriesNew
Data & Analytics
Requirements
- Put people first, and make decisions with the Member's best interests in mind
- Are active learners, constantly looking to improve and grow
- Are driven by our mission to measurably improve health and care each day
- Bring the energy needed to transform health and care, and move and adapt rapidly
- Are laser focused on delivering results for Members, and proactively problem solving to get there
- 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
- 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
- Experience with cloud-based data warehouse: Snowflake
- Experience with relational SQL and NoSQL databases
- Experience with object-oriented/object function scripting languages: Golang, Python, Java, C++, Scala, etc
- Experience with big data tools: Spark, Kafka, etc
- Experience with data pipeline and workflow management tools like Airflow
- Experience with AWS cloud services: EC2, EMR, RDS, Redshift
- Experience with stream-processing systems: Storm, Spark-Streaming, etc