• Us Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 12th Nov 2020

Enterprise Data Quality Analyst
Chicago, IL
12 months
looking for Health Care and with Data Management, Data governance experience.

Required Skills & Qualifications

5+ years’ experience of doing data quality analysis, root cause investigations, and remediation (not application testing).
5+ years’ experience working with data tools such as SQL, R, Python, SAS, Tableau and TOAD
Experience and working knowledge of data in a healthcare data management environment
Experience in migrating manual data quality processes to an automated, sustainable framework

Role Summary

The Enterprise Data Strategy team within Global Data & Analytics (GD&A) is built to help the client drive that improvement in the accessibility and quality of our data assets and tools, and allow us to deliver data solutions faster than we do today. Our ultimate goal is to ensure client’s ability to grow is unconstrained by any limitations of our data. The Enterprise Data Strategy team is comprised of business and technical teams spanning Customer, Provider, Buyer and Intermediary Data Domains as well as foundational enterprise data teams. The Customer Data Domain team establishes customer data strategy through an Enterprise lens and ensures roadmap delivery for all enterprise customer data domain initiatives.
The Enterprise Data Quality Analyst - Customer Data Domain requires a candidate with strong data management background who understands data, data ingestion, proper use/consumption, data quality, and stewardship. In this role you will perform data quality processes, measurements and analyses to assess patterns, identify root cause, define data quality rules, champion automated measurement and partner with stakeholders to identify data improvement opportunities.

Responsibilities

·         Implement data quality rules, automated measurement / monitoring, issues management framework, operational dashboards, and predictive models for proactive data quality assessment and identification of improvement opportunities
·         Work with source systems and downstream data consumers to apply advanced data quality techniques through automation to remediate issues, and implement processes to monitor data quality risks, including:
·         Analyzing data quality results
·         Measuring and auditing large volumes of data for quality issues and improvements
·         Performing root cause analysis of data anomalies
·         Triaging data quality issues and creating remediation plans
·         Evaluating and quantifying business impact of data quality issues and making recommendations for data improvements including required process and system changes
·         Develop data quality policies, procedures, best practices, and related knowledge content
·         Collaborate with stakeholders to ensure data quality best practices are implemented across enterprise data assets
·         Lead efforts to communicate quality of enterprise data assets and the value realized through data improvement efforts
·         Orchestrate data quality work within the Agile framework and other methodologies where required for on-time delivery of data quality measures and results to stakeholders