Sr. Data Engineer

View full description

Requirements:

• 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.
• Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.

Responsibilities:

• 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.