Senior Data Engineer IS - Hybrid

Providence Health & Services is a comprehensive health care organization serving communities across multiple states. The Senior Data Engineer analyzes clinical data, builds data-centric applications and pipelines, and supports healthcare operations using cloud computing, big data, data science, and modern software development practices. The role also mentors less experienced engineers and collaborates with Product, Platform, and Architecture teams.

Responsibilities:

• Apply knowledge of health care and database management to analyze clinical data, and to identify and report trends. Design and build modern data-centric software applications to support clinical and operational processes across all parts of the healthcare system. These applications leverage cloud computing, big data, data science, and modern software development methodologies and frameworks. Builds data pipelines and transformations, data enrichment processes, provisioning layers, ad user interfaces to meet the requirements of key initiatives. Has a demonstrated ability to mentor and assist less experiences Data Engineers and participate in research and development of new technologies to help set up repeatable processes or templates for other Data Engineers to follow. Strongly encourages and places a priority on collaboration with meticulous source control and documentation. An emphasis on simple solutions to complex problems using modern and emerging methods and tools is critical. This position will work closely with the Product, Platform, and Architecture teams to deliver on joint efforts

Requirements:

• Bachelor's degree in computer engineering, Computer Science, Mathematics, Engineering
• 5 or more years of experience as a Senior Data Engineer
• Master's degree in computer engineering, Computer Science, Mathematics, Engineering
• 8 years of Data development experience
• Advanced Hadoop / Spark / NoSQL✔ (Spark, Hadoop ecosystem, Kafka, Flink, NoSQL platforms)
• Advanced SQL + Python ✔ (Python, SQL, Linux-based processing
• OLAP / Cloud Data Warehousing✔ (Snowflake, Synapse, Redshift, BigQuery, dimensional models)
• Unstructured & Multimodal Data Engineering ✔ (EHR/EMR, HL7, FHIR, APIs, clinical notes)
• Modern Application Development Frameworks ✔ (FastAPI, Flask explicitly listed and used)
• Modern ETL / ELT Tooling✔ (ADF, Glue, Airflow, dbt, NiFi, Informatica, Fivetran)
• AI/ML + LLM / Prompt Engineering✔ (LLM pipelines, RAG, LangChain/LlamaIndex, embeddings, vector DBs)