Data Engineer

About the Company:

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.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.

For company details visit our website: www.webmd.com / www.internetbrands.com

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

Experience: 4+ years

Work timings: 2 PM to 11 PM IST

Position Requirements:

Minimum 4+ years of experience on PostgreSQL or any Unix based relational database.

Minimum 2+ years experience with Pentaho Data Integration Tools or any ETL/ELT tools like Talend, Informatica, or HOP.

Hands on Experience working with Application Developers as well as teams outside of IT (i.e. Business Intelligence, Finance, Marketing, Sales).

Advanced understanding of SQL.

Experience with Big Data platforms (Hadoop, Hive, GCP) is good to have.

Experience with reporting and Data Visualization platforms (Tableau, Pentaho BI) will be an added advantage.

Experience with Python, Java or other development is good to have.

Strong communication and documentation skills.

Willingness to learn new technologies.

Role & Responsibilities:

Design, Develop & Support multiple data engineering projects with heterogeneous data sources.

Analyze Business Requirements, design and implement required data model and Build ETL/ELT strategies.

Lead data architecture and engineering decision making/planning.

Translate complex technical subjects into terms that can be understood by both technical and non-technical audiences.