Senior Health Data Modeler or Principal Healthcare Data Analyst

Role: Senior Health Data Modeler or Principal Healthcare Data Analyst Location: MN101 (100% Telecommute / Remote)

Work Hours: 9:00 AM 5:00 PM

Certifications/Licenses Required: None

Project Summary & Initiative

Client is currently seeking a hands-on Senior Health Data Modeler to support our CT EDW within the Enterprise Datawarehouse and Analytics group. The Data Modeler will work with large healthcare datasets and will translate the client's business requirements into enterprise systems, applications, or process designs for large complex health data solutions. The role will drive and support initiatives for the CT EDW as well as participate in the wider EDW group s areas of data usage and governance, information management, privacy and security, SOA, data analytics and visualization, and information modeling.

Ideal Candidate Background

The ideal candidate is a highly technical Data Modeler with robust Medicaid and Healthcare experience. This specific background is what will set a candidate apart from others.

Key Responsibilities

On a daily basis, the candidate will be expected to complete the following core responsibilities:

• Develop and deliver long-term strategic goals for data architecture vision and standards in conjunction with data users, clients, and other key stakeholders.

• Lead data architecture, data modeling, and data movement initiatives to enhance the architecture of the data warehouse which supports analytics for Medicaid, Medicare, and Commercial healthcare data (including domains such as claims, provider, TPL, and member information subject areas).

• Create an end-to-end vision on how logical design translates into one or more physical databases, and how the data will flow through the successive stages.

• Analyze and translate business needs into long-term solution data models.

• Evaluate existing data systems and work closely with the development team to create conceptual data models and data flows.

• Ensure that data strategies and architectures are in regulatory compliance. Recognize and identify potential areas where existing policies and procedures require change, or where new ones are needed.

• Oversee the mapping of data sources, data movement, interfaces, and analytics, with the goal of ensuring data quality.

• Create and maintain data model and metadata policies and procedures for functional design.

• Provide technical recommendations and engage with other ETL Architects, Business SMEs, and other stakeholders throughout the Solution/Data Architecture and implementation lifecycle to recommend effective solutions for developing high-performance and highly scalable data solutions (data marts/warehouse, data mining, and advanced analytics).

• Address data-related problems regarding systems integration, compatibility, and multiple-platform integration.

• Develop and implement key components as needed to create testing criteria to guarantee the fidelity and performance of data architecture.

• Document data architecture and the enterprise environment to maintain a current and accurate view of the larger data picture, creating an environment that supports a single version of the truth and is scalable to support future analytical needs.

• Communicate with the customer and project team in a timely manner and escalate issues and risks appropriately.

Required Skills & Attributes

• Top Skill / Experience: 5+ years of experience specifically utilizing Erwin data modeler.

• Core Competency: Expertise in Data Modeling, Data Strategy, and Roadmap creation for large and complex health entities and systems. Must have implemented large-scale end-to-end Data Management & Analytics solutions for more than one large client.

• Domain Expertise: Strong Healthcare domain knowledge specifically utilizing Medicaid, Medicare, and Commercial healthcare data sets.

• Security & Compliance: Strong knowledge of regulatory security requirements regarding HIPAA, PHI, PII, and other health care data security standards.

• Data Modeling: Expertise with normalized OLTP, OLAP, MDM, and Dimensional modeling techniques, Star schemas, slowly changing dimensions (SCDs), role-playing dimensions, dimensional hierarchies, and data classification.

• Database & SQL: Expert-level SQL skills with direct experience writing complex analytic queries, stored procedures, DDL, DML, and DCL. Thorough knowledge of query optimization techniques with the ability to write code to ANSI standards and inspect code written by other developers.

• Data Management: Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, MDM, Data Archival, and Data Migration strategies using appropriate tools.

• Soft Skills: Strong problem-solving, influencing, communication, and presentation skills. Must be a self-starter.

Preferred Skills (To set candidates apart)

• Experience with Microsoft Azure cloud infrastructure and services (Azure Data Lake Storage, Azure Data Factory, Purview, Azure Maps, etc.).

• Experience with Snowflake DBMS.

• Experience with PowerBI or Tableau.

Team Structure & Interview Process

• Team Breakdown: You will be working alongside a Data Manager, Data Modeler, Data Integration Lead, and Data Engineers.

• Interview Process: Candidates should expect a 3-round interview process conducted via Video. Please note that the interviews will be very technical in nature.