Job Title –
Data Engineer
Overview Of Providence
At Providence, we use our voice to advocate for vulnerable populations and needed reforms in health care. We pursue innovative ways to transform health care by keeping people healthy, and making our services more convenient, accessible and
affordable for all. In an increasingly uncertain world, we are committed to high-quality, compassionate health care for everyone—regardless of coverage or ability to pay. We help people and communities’ benefit from the best health care model for the future—today.
Together, our 119,000-plus caregivers/employees serve in 51 hospitals, more than 1000 clinics and a comprehensive range of health and social services across Alaska, California, Montana, New Mexico, Oregon, Texas and Washington in United States.
Providence Information Service (commonly known as Information technology) is aimed to digitally enable our vision of Health for a better world. We make use of multiple technologies spread across Microsoft, Oracle, JAVA, Python and many new open sources.
Providence Global Center recently launched in Hyderabad, India as Global Capability Center for Providence looking to leverage the India talent to help meet our global vision and scale our Information Services and products to the world of Cloud.
About Healthcare Intelligence
Healthcare Intelligence is the pillar that focuses on creating intelligent data products within Providence and provides unique opportunities in Data Engineering, Operations, Data Science, BI Reporting and Data Analytics on cloud stack. We are a group of data professionals who work towards enabling decisions that improve patient and caregiver experience.
About The Role
A Data Engineer is responsible for designing and modelling Data lake solutions/data ingestion pipelines by collaborating with our customers and understanding requirements on digital transformation. Able to navigate through ambiguous situations, to deal with aggressively changing setting. Th
📌 Data Engineer 1 (Hyderabad)
🏢 Providence India
📍 Hyderabad
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