Principal data engineer(azure)

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 technological stack spread across Microsoft, Oracle, JAVA, Python and many new open sources.

Providence Global Centre recently launched in Hyderabad, India as Global Capability Centre 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.

Organization Background:

The ESI Enablement & Platform Technology - LES Team provides analytical services to business units and IS Stakeholders. In this role you will engineer, develop, and support the complete lifecycle of the Enterprise Data Archival and Electronic Data Conversion service, Caregiver Training, Data Warehouse, and a variety of Azure Services for ETL/ELT processes. The successful candidate will possess a strong understanding of Azure Data Services, Data Analysis, and ability to articulate findings and recommendations to stakeholders.

What will you be responsible for Strong knowledge of SQL, Azure SQL, TSQL Strong knowledge of database, datawarehouse and data analysis Strong knowledge of Databricks, python, spark. Working experience in writing scripts on C# or similar languages for API development Integrate unstructured data from multiple systems to create a single source of truth Develop, monitor, and manage report curation and data modeling Creating/implementing/Adopting API Governance and Standards for Data Analytics Creating APIs to integrate unstructured data from a variety of systems to create a single source of truth (Sail Point, Service Now, Project Online, ADO, Intune, Azure licensing, and other systems of records for single/bi-direction data sets) Working on Azure Services like Azure Data Factory, Azure Workbook, Log Analytics, Azure Functions, and other data analytics tools Leveraging various Azure Services such as Azure Storage, Logic Apps, Data Factory, Azure SQL Saa S, Runbooks, Automation, Graph API, and various other data tools Developing/maintaining microservice automation (Prisma Cloud/Kubernetes) Working experience in data visualization, Power BI, writing complex SQL queries

What would your day look like? Work closely with service teams to determine project engagement and priority, business data reporting and analysis requirements Gather Requirements, Data analysis and modelling Create scripts to support enhancements Work with external vendors on bi-directional API integrations Collaborate with DWH and Reporting teams on data analysis and integrity Gather requirements, develop, and implement solutions across all endpoint technologies in the Microsoft stack

Who we are looking for? Minimum 6-12 years of experience in Azure Data Engineering Minimum 6-12 years of experience in BI Development 6-12 years of experience working in cloud technologies such as Azure/AWS/Google cloud service Experience with Apache Spark and Azure Databricks Working knowledge of Microsoft Fabric Ability to troubleshoot technical problems, demonstrate problem solving Ability to effectively communicate and excellent interpersonal skills Experience working in Agile/sprints in a global team setup Bachelor’s Degree in Computer Science, Data Analytics, Business Management, or IS