Royal Jay is looking for a data and BI engineer to work on our Inflight platform. Inflight enables health systems to identify high-value opportunities in care coordination, cost & utilization, and population health management.
As a data engineer, your day to day work enhances our standard claims and clinical model, builds data ingress and egress processes through Azure Data Factory (ETL), and implements new healthcare analysis models. You will work closely with our software engineers to deliver this data to customers on the inflighthealth.com platform.
Responsibilities
Responsible for ingesting, validating, regression testing, and modeling claims and EHR data into a canonical format used for use in population health analysis. Building ingesting strategies and models specific to payers and clients.
Build & maintain automated ingestion processes for raw claims, clinical and unstructured data through Azure Data Factory. Data is ingested from partners into the Inflight data warehouse for additional analysis and model building.
Build facts and dimensions in the warehouse to supply data to Azure Analysis Services.
Modeling relational and star schemas to support specific clinical, quality, and performance standards (HEDIS, Stars, NQF).
Performance Profiling around Azure SQL. Building automated testing to reduce data regressions.
Advise Inflight partners on methods for sending, shaping, and modeling data for ingest/egress to the Inflight platform. Documenting key processes and training other engineering team members on the use of the model.
Qualifications
Expert in T-SQL, Azure SQL, Warehousing
Relational & Star Schema (Facts & Dimensional) Modeling
SSIS, SSAS Tabular (DAX)
Time Series Data Modeling and Analysis
Experience in designing recurring ETL processes
Data profiling to identify anomalies
Automation of Data Integrity Testing
Understanding of Azure Security & HIPAA Security Compliance
Bachelors or advanced degree in Information Science, Operations Research, Computer Science or Statistics
Nice to Have
Experience in healthcare data formats. Medicare/Commercial claims, HEDIS, NQF, EHR clinical data, ADTs, HL7, CDA.
Experience in healthcare concepts such as patient/provider attribution, record linkage, admission and emergency department classification, RAF and risk stratification, HCCs, care management stratification, population health, and value-based care.
Experience building or experimenting in Azure BI across various platforms including, Data Factory, Data Lake, Azure Synapse, U SQL, Data Flow, Azure SQL Server. MDX, R, Python, C#, knowledge of networks, and server administration.