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# Data Engineer

- **Company:** Recruiting from Scratch
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Code Review, Information Engineering, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Warehousing, Document-Oriented Databases, Apache Hadoop, Monitoring of Systems, Python (Programming Language), Systems Development Life Cycle, SQL Databases, Data Streaming, Data Processing, Google Cloud, Data Storage Technologies, Apache Spark, Health Level Seven International, Data Management, Data Pipelines, Programming Languages
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/data-engineer-san-francisco-ca--9a855ed4-4424-4bb6-a652-c58341867cb3

## About the Role

Healthcare, Seed Funding, Intelligent Network, Patient Care, Startup, Healthcare Providers, Data Management, Scalable System Development, Data Analysis, Cross-Functional, * 3-5 years of experience in data engineering or a related field.

 * Proficiency in SQL and experience with ETL tools and data warehousing solutions.
 * Strong understanding of data modeling concepts and best practices.
 * Experience with programming languages such as Python or Java for data manipulation and analysis.

Preferred

 * Familiarity with cloud platforms like AWS, Azure, or Google Cloud.
 * Experience working with big data technologies such as Hadoop or Spark.
 * Knowledge of healthcare data standards and regulations.

## Description

* Design, develop, and maintain scalable data pipelines to support data integration and analytics.
 * Collaborate with cross-functional teams to define data requirements and ensure optimal data flow.
 * Implement data quality checks and monitoring systems to maintain high standards of data integrity.
 * Utilize cloud-based technologies to optimize data storage and processing capabilities.
 * Analyze large datasets to identify trends and insights that drive business decisions.
 * Participate in code reviews and contribute to best practices in data engineering.
 * Document data architecture and processes to ensure clarity and continuity across teams.