Principle Data Engineer

Position: Principle Data Engineer

Remote

6 months + extensions.

Project -

Clinical Data Analytics Team Overview

• The only team responsible for end-to-end development within the organization.
• Builds data products for the Chief Medical Officer (CMO), with a strong focus on delivering actionable insights.
• Develops Tableau dashboards on top of these data products to enable visualization and reporting.
• Operates through two development pods, each working on separate data models.
• Currently addressing significant technical debt by consolidating data into an enterprise data zone for better leverage.
• Goal is to clean and standardize data to support downstream systems and create a scalable, enterprise-ready solution.

Tech Stack:

• DBT
• Snowflake
• GIT
• EPIC - Clinical Data - Time you were admitted to the hospital to the time you leave the hospital. Not claims EPIC DATA.
• Clarity - must have
• Caboodle. - must have.
• Data Profiling, bleeding a tad into the analyst realm
• Nice to have:
• CI/CD pipeline experience
• Healthcare and/or clinical data
• Epic
• Azure DevOps
• Data Modeling

• Perform EDW ETL/ELT ingestions and integrations to ensure support data and analytic needs.
• Build and enhance standard solution that provides efficient and scalable ETL/ELT solutions from multiple data sources.
• Ensure the quality of data assets and robustness of data engineering processes.
• Experience with change control, release management and other ITIL processes.
• Participate in building out EDW on Snowflake, expanding and optimizing the data ecosystem, as well as optimizing data engineering processes.
• Support BI Developers, Data Architects, Data Analysts and Data Scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
• Conduct ETL solution, code, and pre-prod review to ensure optimal data delivery architecture is consistent throughout ongoing projects.
• Perform troubleshooting on ETLs and related components.
• Identify application bottlenecks and opportunities to optimize performance.

Qualifications:

• 7+ plus years of experience designing and building data ingestions and data integration solution for Enterprise Data and Analytics Solutions
• 3+ years of experience with developing data pipelines using on Snowflake features ( Snowpipe, SnowSQL, Snow Sight, Data Streams )
• 2+ years of experience with developing models in DBT
• Demonstrate good knowledge of scrum & agile principles
• Experience with Azure DevOps, Azure Git and CI/CD data pipeline integrations.
• Demonstrates good knowledge of cloud computing platforms such as Azure
• Experience of support and enhance existing Enterprise Data Warehouse or Data Lake
• Ensure designed systems are highly reliable, self-recovering, and require little or no supporting manpower
• Familiar with change control, release management, and other ITIL methodology
• Deep experience in traditional Data Warehousing & Cloud data warehousing
• Mastery of SQL, especially within cloud-based data warehouses like Snowflake
• Experience developing data pipelines using Snowflake features (Snow pipe, SnowSQL, Data Streams, Snow Sight)
• Experience with logical and physical data modeling
• Healthcare experience, most notably in Clinical data, Epic, Payer data and reference data is a plus but not mandatory.
• Ability to clearly and concisely communicate complex technical concepts to both technical and non-technical audiences
• Proven verbal, communication, and presentation skills
• Proven ability to work independently.