Data Engineer

Are you looking to take off your career to gain unique experiences?

Passionate to contribute to the digital transformation of Health care? At Providence, we are grounded in our goal to serve all as we engineer the future of healthcare. We build the tech to enable our caregivers deliver better healthcare outcomes and enhanced continuity of care. We focus on engineering, modern infrastructure, data intelligence, cloud, digital innovation, professional services, cyber security and application development & support. Providence Global Center will help achieve our vision of health for a better world and be at the forefront of innovation in the healthcare industry. Enterprise Services and Infrastructure (ESI) team provides foundational infrastructure of Cloud Services, Network Connectivity, Data Center Hosting, Voice, Collaboration Applications, and End User Computing enabling our caregivers, patients, physicians, and Community Technology partners to achieve our mission. Data Engineering is at the core of the overall services acting as a horizontal function to enable data driven intelligence and decision-making.

About the Role We are looking for a results-driven AI + Data Engineer to build and scale modern, intelligent data platforms. This role combines data engineering on Snowflake + Azure with hands-on development of AI/GenAI solutions such as LLM-based applications, RAG pipelines, and intelligent data products.

Key Responsibilities

• Develop and maintain scalable data pipeline using Snowflake and Azure ecosystem
• Implement high quality data ingestion and transformation frameworks for structured and unstructured data
• Develop Gen AI solutions using LLMs, including RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases
• Build and optimize embedding pipelines and vector search solutions for semantic retrieval
• Create standard processes and metric definitions for optimized analytics, reporting and downstream consumption
• Create and execute unit testing and end-to-end integration test plans for each block of data and analytics pipelines.
• Optimize performance of data pipelines and queries to meet SLAs

Must‑Have Qualifications

• 2-4 years total experience in data engineering on cloud platforms, with Applied AI.
• Min 2 years of experience in

Snowflake with exposure to warehouse configuration, schema design, performance tuning; stored procedures/tasks; loading strategies. Exposure to Snowflake Cortex AI.

• Experience working on

Azure cloud platform and ADLS.

• Experience in building

Gen AI solutions using

LLMs, RAG pipelines, vector DBs and embeddings.

• SQL/Python/PySpark : Design and implement scalable data processing solutions using SQL, Python, and distributed compute frameworks, including unit/integration tests.
• Built and deployed

RESTful APIs for data ingestions, Gen AI applications and LLM inference endpoints for internal workflows.

• Version control & CI/CD : Exposure to Git, pull requests, automated deployment pipelines.
• Maintain a results-oriented mindset with strong analytical and problem-solving skills.
• Strong communication and collaboration skills to work in an Agile and global setting.
• Good to have: Experience in Healthcare Industry