Description

About WebMD:

WebMD Health Corp., an Internet Brands Company, is the leading provider of health information services, serving patients, physicians, health care professionals, employers, and health plans through our public and private online portals, mobile platforms, and health-focused publications. The WebMD Health Network includes WebMD Health, Medscape, Jobson Healthcare Information, prIME Oncology, MediQuality, Frontline, QxMD, Vitals Consumer Services, MedicineNet, eMedicineHealth, RxList, OnHealth, Medscape Education, and other owned WebMD sites. WebMD®, Medscape®, CME Circle®, Medpulse®, eMedicine®, MedicineNet®, theheart.org®, and RxList® are among the trademarks of WebMD Health Corp. or its subsidiaries.

For Company details, visit our website: www.webmd.com

Education: B.E. Computer Science/IT degree (or any other engineering discipline)

Experience: 4 + years

Work timings: 2 PM to 11 PM

Position Requirements:

• Experience with data QA and ETL/ELT (Data Pipelines) QA
• Proficient in SQL (analytical functions, trending, windowing) - Traditional (For e.g., MSSQL, Oracle, PostgreSQL) Or Columnar (Like Vertica, Amazon Redshift)
• Experience working closely with teams outside of IT (i.e., Business Intelligence, Marketing, AdOps, Sales)
• Strong understanding of the Web analytics, metrics, KPIs and reporting
• Experience with automating regression tests, reporting platforms (For e.g. Tableau or Pentaho BI) and ETL tools (For eg. Pentaho or Talend) will be an added advantage
• Understanding of Ad stack, Email data and data (Ad Servers, DSM, DMP, etc) is good to have

• Performing statistical tests on large datasets to determine data quality and integrity.
• Evaluating system performance and design, as well as its effect on data quality.
• Collaborating with database developers to improve data collection and storage processes.
• Running data queries to identify coding issues and data exceptions, as well as cleaning data.
• Gathering data from primary or secondary data sources to identify and interpret trends.
• Reporting data analysis findings to management to inform business decisions and prioritize information system needs.
• Documenting processes and maintaining data records.
• Adhering to best practices in data analysis and collection.
• Keeping abreast of developments and trends in data quality analysis.