Data Engineer

The Data Quality Team provides tools, processes, and expertise to help reduce the time and cost to implement and maintain our data products while ensuring high quality data that helps differentiate our analytics.

The Data Quality Engineer (DQE) role combines data engineering and analytic skills with a sound understanding of the processes and data that our product and services teams rely on to help our health system clients make sound data informed decisions that are based on high quality data. The primary accountability of the DQE is to ensure that all data quality infrastructure and insight is highly available, reliable, and actionable for our primary users; this work will include building, deploying, and maintaining infrastructure and analytics as well as working across the company with other teams to do so.

Duties &; Responsibilities

• Development, deployment, maintenance, and support of Data Quality Data Pipeline (standard
  data model, client-side processing, extract from client, ingest into central environment, and cross-
  client aggregation).
• Development, maintenance, and support of Data Quality Central Power BI application
  (centralized data quality validation and monitoring application used by Catalyst product teams).
  Assist product and services teams in development and maintenance of their data quality check
  libraries.
• Review and deploy data quality check libraries to client environments on behalf of product and
  services teams; provide support when/where required.

Required Skills

• Intermediate level in Structured Query Language (SQL).
• Intermediate level at developing data sets, reports, and dashboards in Power BI.
• Strong experience working with Azure DevOps Boards, Repos, and Pipelines.
• Experience working in both SQL Server and Azure Synapse technologies.
• Experience identifying data quality gaps or issues and writing checks to facilitate validation and monitoring that covers the gap.
• Demonstrated ability and desire to provide excellent customer service.
• Demonstrated ability and desire to collaborate and work within and across teams.
• Demonstrated ability and desire to efficiently learn and effectively leverage new concepts, skills and technologies.
• Ability to explain data quality concepts, tools, and processes to technical and non-technical audiences.
• Experience working with DOS Metadata to integrate with, leverage, or extend DOS functionality.
• Software engineering skills and/or software support experience.
• Ability to work independently with general guidance through daily and weekly coordination meetings.

Really nice to have

MDM (Master Data Management)