![]() ![]() Kaiser Permanente conducts compensation reviews of positions on a routine basis.Investigates and resolves patient/family member concerns regarding patient care. Researches, identifies, and implements best practice models of other units. Works with health care providers outside of the unit, to achieve optimal patient care across the continuum.Ensures coordinated plans of treatment, customer focused care and cost effective utilization of services. Monitors the quality of service and utilization standards and assumes specific responsibility for patient care at the unit level.Supervises the daily unit operations, including human resources management, department and employee safety programs, and risk management.Monitors the allocation and utilization of personnel based on continual changes in patient population/needs and provides the best level of patient care while identifying savings opportunities.Supervises a single unit (8 to 24 hours) of approximately 20 - 60+ employees. Develops and implements action plans to improve staff development.Ensures the highest quality of care is provided and is in compliance with federal, state, and local regulatory requirements and established departmental policies and procedures. Manages the units day to day clinical operations including practice standards, staffing, payroll, budgets, fiscal management, and quality improvement. ![]() Supervises the day to day shift activities. Manages activities of the unit(s), monitors quality, service and utilization standards. Experience using airflow at scale, with integration to meta-data & lineage systems of record.Experience with Big Data Platforms, Data Warehousing, Data Lake, Data Mart, DataMesh/Data Hub concepts.Strong experience of event streaming platforms like Kafka, Kafka Connect, ksql.Experience working with Python for Spark (Pyspark).Experience with Azure Data services (ADLS, ADF, Event Hub, Azure functions).Experience with data modeling (OLTP & OLAP) and data formats including Avro, Parquet, etc.Experience building data pipelines leveraging Spark (Azure Databricks or Apache Spark), Airflow.Experience in Azure, Spark, data modeling, various data services on Azure. ![]()
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