Data Engineer - Remote

Experteer Overview In this role you will design, build, and maintain scalable data pipelines on an Azure-based platform to support batch and real-time analytics. You will collaborate with data engineers, data science, and reporting partners to meet evolving data requirements and enforce governance, quality, and performance standards. The role focuses on end-to-end pipeline development, medallion architecture, and reliable data delivery at scale. You will work in a flexible, remote-friendly environment with opportunities to impact health care analytics and decision-making. Compensation / Benefits * Design, develop, and maintain batch and streaming data pipelines using Azure Data Factory and PySpark (Databricks) * Implement real-time ingestion with Spark Structured Streaming and schedule batch ETL jobs * Apply Medallion Architecture (Bronze/Silver/Gold) for data processing and data quality checks * Optimize Spark jobs, tune configurations, and manage resources for high throughput and low latency * Build and maintain ETL transformations, handle data from APIs, databases, file feeds, and IoT streams * Implement data quality validation, monitoring, and automated alerts * Utilize modern pipeline frameworks (Delta Live Tables, Lakehouse pipelines) where applicable * Document workflows, enforce data governance, and ensure data lineage and security controls Tasks * 3+ years in data engineering designing and implementing data pipelines and ETL * 2+ years SQL for data manipulation and query optimization * 1+ years Azure, Databricks or equivalent cloud data platform experience * Proficiency in Python and PySpark for batch and streaming transformations * Experience with streaming technologies (Spark Streaming, Kafka, Azure Event Hubs) * Strong collaboration in agile teams and ability to communicate with both technical and non-technical stakeholders * Experience with data quality validation and data governance practices Key requirements * comprehensive benefits package * equity stock purchase * 401k contribution * remote-friendly / flexible work * incentive and recognition programs

latency * Build and maintain ETL transformations, handle data from APIs, databases, file feeds, and IoT streams * Implement data quality validation, monitoring, and automated alerts * Utilize modern pipeline frameworks (Delta Live Tables, Lakehouse pipelines) where applicable * Document workflows, enforce data governance, and ensure data lineage and security controls Tasks * 3+ years in data engineering designing and implementing data pipelines and ETL * 2+ years SQL for data manipulation and query optimization * 1+ years Azure, Databricks or equivalent cloud data platform experience * Proficiency in Python and PySpark for batch and streaming transformations * Experience with streaming technologies (Spark Streaming, Kafka, Azure Event Hubs) * Strong collaboration in agile teams and ability to communicate with both technical and non-technical stakeholders * Experience with data quality validation and data governance practices Key requirements * comprehensive benefits package * equity aa and purchase * 401k contribution * remote-friendly / flexible work * incentive and recognition programs