Data Analytics Engineer; Hybrid

Company: North East Provider Solutions Inc.

Category: Finance/Info Systems

Department: DMA-Data Management &Analytics

Union: No

Position: Full Time

Hours: 40

Shift: Day

Posted Date: Oct 07, 2026

Hiring Range: $100,287 - $126,083

* If you are hired by WMCHealth, your final base salary will be determined based on job-related factors, including employment status (full-time, part-time or per diem), relevant skills, qualifications and experience. Consistent with our commitment to pay equity, we also consider internal equity among similarly situated employees when determining final compensation.

• Build the infrastructure required for optimal extraction, loading, and transformation (ELT) of data into our enterprise data warehouse (EDW) from a wide variety of data sources using SQL and Cloud data warehousing technologies (Azure, AWS, Snowflake, etc.).
• Create and maintain optimal data pipeline ingestion architecture for various unstructured and structured data sources.
• Strong business process acumen with the ability to attribute how specific clinical or non-clinical business processes generate data.
• With a comprehensive understanding of how our operational processes generate data, develop the transformation logic to establish structured and analytical data repositories across various domains.
• Using data orchestration and scheduling techniques, combine and organize siloed data from multiple data storage locations, making it available for data analysis tools and enabling automation.
• Develop and maintain front-end analytics tools and dashboards (Tableau/Power BI) that utilize the data pipeline to provide actionable insights into operational performance and other key business performance metrics.
• Successfully implement sound data cataloging and analytics development best practices to create organized inventories and source control which aid in data governance.
• Ensure data quality & governance at the enterprise level by utilizing data lineage techniques and following standard data documentation practices.
• Collaborate with stakeholders including Executive leadership, Operations Management, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Ensure internal and external data security standards are maintained to safeguard our enterprise and patient data.
• Provide recommendations to enhance our data engineering techniques and architecture design.
• Create data tools and collaborate with management engineering, analytics, and data scientist team members to assist them in building and optimizing various analytics solutions.
• Utilize agile skills that draw from other disciplines such as management consulting, business administration, organizational development, information technology, and computer science.

Job Summary:

As an Analytics Engineer within the Operational Excellence & Enterprise Analytics Department, you will be responsible for expanding and optimizing our network enterprise data warehouse, thus enabling our organization to make data-driven decisions and improvements. The ideal candidate has skills as a data pipeline developer and data wrangler who enjoys optimizing data systems and building them from the ground up. You must be self-directed and comfortable supporting the data needs of multiple teams and systems in the clinical and non-clinical domains.

The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to enable data-driven decision making for strategic, operational, and clinical domains.

Responsibilities:

• Build the infrastructure required for optimal extraction, loading, and transformation (ELT) of data into our enterprise data warehouse (EDW) from a wide variety of data sources using SQL and Cloud data warehousing technologies (Azure, AWS, Snowflake, etc.).
• Create and maintain optimal data pipeline ingestion architecture for various unstructured and structured data sources.
• Strong business process acumen with the ability to attribute how specific clinical or non-clinical business processes generate data.
• With a comprehensive understanding of how our operational processes generate data, develop the transformation logic to establish structured and analytical data repositories across various domains.
• Using data orchestration and scheduling techniques, combine and organize siloed data from multiple data storage locations, making it available for data analysis tools and enabling automation.
• Develop and maintain front-end…