Data Engineer I

Before you apply

Job source

Himalayas

Applying on

himalayas.app

Workplace

Fully remote

US state

Nationwide remote

Category

Data Entry

Link last checked

Not checked yet

Posted

4 hours ago

Closes

11/19/2026

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About the role

Vālenz Health® is the destination for employers, brokers, payers, and providers to reduce costs, improve quality, and elevate the healthcare experience. Through advanced technology and clinical expertise, Valenz creates a distinctly different approach to a complex healthcare system. With our solutions, we execute across the entire healthcare journey — from member experience to payment integrity, provider quality, and plan performance. With one of America’s largest cost, quality and utilization datasets, we create greater transparency, flexibility, and cost containment — empowering members and employers with the information they need to make smarter, more cost-effective decisions. About This Opportunity: As a Data Engineer I, you’ll help develop and maintain scalable data pipelines and solutions within our modern, cloud-based data platform. You’ll transform, validate, and integrate healthcare data from multiple sources to ensure accurate, reliable, and accessible data for analytics, reporting, and broader business needs. You’ll also partner with Analytics and other cross-functional teams to translate data requirements into effective solutions while supporting the continued growth and evolution of our cloud-based lakehouse architecture. Things You’ll Do Here: Develop, maintain, and enhance data pipelines that ingest, transform, validate, and integrate data from multiple internal and external sources. Support the migration of on-premise SQL Server data systems to a cloud-based lakehouse architecture using Azure Databricks and Delta Lake. Develop and maintain ETL/ELT processes using SQL, Python, PySpark, and Spark SQL. Apply established lakehouse and Delta Lake architecture standards, including schema enforcement, data quality controls, ACID transactions, and data versioning. Build and maintain data models that support analytics, reporting, and data warehousing needs. Implement data quality checks, validation processes, and monitoring to ensure the accuracy, completeness, and reliability of data pipelines. Orchestrate and monitor data workflows using Databricks Workflows, Apache Airflow, or similar technologies. Troubleshoot pipeline failures, data quality issues, and performance concerns, identifying root causes and implementing appropriate solutions. Support the optimization of data pipelines for performance, scalability, reliability, and cost efficiency. Collaborate on CI/CD practices for data engineering solutions, including source control, testing, deployment, and version management. Partner with data analysts, data scientists, and business stakeholders to understand data requirements and develop supporting pipelines and data structures. Document data pipelines, transformations, technical processes, and data structures to support maintainability and knowledge sharing. Participate in code reviews, testing, and Agile development processes to support consistent engineering standards and continuous improvement. Stay current on data engineering technologies and contribute ideas for improving the organization's evolving data platform. Perform other duties as assigned. Reasonable accommodation may be made to enable individuals with disabilities to perform essential duties. What You’ll Bring to the Team: Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related quantitative or technical field, or equivalent practical experience. 1+ years of experience in data engineering, software development, data analytics, or a related role involving similar technical responsibilities. Working knowledge of SQL and Python, with experience using these technologies to manipulate, transform, or process data. Experience developing or supporting ETL/ELT processes, data pipelines, data integrations, or similar data engineering solutions. Understanding of relational databases, data modeling concepts, and data warehousing principles. Ability to troubleshoot data and technical issues, investigate root causes, an

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