Senior Data Engineer - Medical Economics; Hybrid

Responsibilities & Qualifications

PURPOSE:

The Senior Data Engineer, working within the Finance Data Systems and Decision Support area, is a highly motivated professional responsible for developing innovative and complex data solutions and applications to support Trend analytics in medical economics. With a critical eye towards data integrity, deep understanding of provider, claims, enrollment data, utilization measures, and practical experience working with health care data, the Senior Data Engineer will work closely with actuaries to produce trend analytics tools, dashboards, and assist with ad hoc reporting and analysis.

Additionally, the Senior Data Engineer will partner with actuaries to support the financial impact analysis related to the building of and changes to provider networks and contracting.

The Senior Data Engineer is expected to have a strong understanding of the business and financial health care data and performs analysis on the data to validate accuracy and proper reporting based on established business rules for their own work and that of colleagues.

The Senior Data Engineer is expected to be a self-starter. By learning from the existing processes and analytical tools, the Senior Data Engineer can quickly grow and become the SME and go-to person in the subject matter with minimal supervision under the manager. Excellent critical thinking skills and problem-solving skills are necessary to be successful in the role.

The Senior Data Engineer is expected to make decisions on the appropriate data sources, the optimal approach to solving business problems, and to ensure that results are tied to appropriate controls.

The Senior Data Engineer is expected to be extremely proficient in SQL with practical experience in applying complex business rules and advanced commands against large amounts of data to optimally produce desired results. The Senior Data Engineer is expected to be proficient in using complex Excel functions for data analytics, reporting and presentation of data results. Experience in Microsoft business intelligence tools is beneficial, specifically strong knowledge and experience with SSAS (SQL Server Analysis Services) and Power BI.

The Senior Data Engineer is expected to have a firm understanding of the fundamentals of actuarial and financial analytics. This includes familiarity with actuarial terminology and basic calculations as well as with the underlying health care data being used for analysis to be able to explain reasons for outliers and to generally support in-depth questions and analytical results.

The Senior Data Engineer will be responsible and accountable for all phases of the System Development Life Cycle. This requires an understanding of business needs, the data needed to respond to the request, and the ability to execute on the building and delivery of accurate and timely reporting and data solutions.

The Senior Data Engineer is also expected to mentor staff, provide guidance on projects, and represent the Finance Divisions interests during interactions throughout Care First.

This is a fast-paced, collaborative, and iterative environment requiring quick learning, agility, and flexibility.

• Develops and maintains health care data model and solutions to enable business partners build analytics framework and make data-driven business decisions. Works as the liaison translating the business partners data need with underlying infrastructure systems (e.g., data warehouses, data lakes). Prepares and manipulates data using multiple technologies.
• Interprets data, analyzes patterns using various data quality check techniques, and provides ongoing reports. Executes quantitative analyses that translate data into actionable insights. Provides analytical and data-driven decision-making support for key projects. Designs, manages, and conducts quality control procedures for data sets using data from multiple systems.
• Develops data models by studying existing data warehouse architecture; evaluating alternative logical data models including planning and execution tables; applying metadata and modeling standards, guidelines, conventions, and procedures;…