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 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.

Qualifications/Requirements

Experience:

Minimum of 1 year of experience in an Analytics Engineer role, with an undergraduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field, required.

Proficiency in SQL, required
CI/CD development experience for data transformation with SQL, highly preferred
Experience with Cloud Data Warehouse architecture (Snowflake/Azure), preferred
Experience with Python, R, or other programming language, preferred

Education:

Bachelor’s degree, required

, Master’s degree, preferred. Licenses / Certifications:

N/A

Skills:

Experience in SQL development, table design, pipeline design and build, pipeline monitoring, orchestration & scheduling, data profiling, expertise in analyzing data to identify gaps and inconsistencies, troubleshooting, dashboard development/visualization, Cloud EDWs (Snowflake/Azure preferred), Data modeling, Data documentation, SSMS, SQL Server, SSIS Visual Studio. Excellent written and verbal communication with a strong drive for perfection/professionalism in delivery and presentation. Proven ability to work both independently on projects and as part of a larger team. Advanced proficiency in statistics and statistical software with an ability to visualize data for improvement/performance monitoring.

Special Requirements

Physical Requirements:

Physical Activity (please check one box):

☐ Sedentary Work

(involves sitting most of the time, occasionally walking and standing; requires lifting no more than 10 pounds at a time and/or occasionally lifting or carrying objects)

☒ Light Work

(involves lifting no more than 20 pounds at a time with frequent lifting or carrying of objects weighing up to 10 pounds; requires moderate mobility to different work locations)

☐ Medium Work

(involves substantial physical activity and mobility; and lifting no more than 50 pounds at a time with frequent lifting or carrying of objects weighing up to 25 pounds.)

☐ Heavy Work

(involves some type of manual labor including operating heavy machinery/ equipment or physical labor; requires lifting no more than 100 pounds at a time with frequent lifting or carrying of objects weighing up to 50 pounds)

Data Analytics Engineer (Hybrid)

Job description