Vālenz® Health
Vālenz® Health is a comprehensive health plan solutions provider that offers a fully integrated platform designed to simplify the complexities of healthcare for employers, payers, providers, and members. The company focuses on enhancing quality and lowering costs through data-driven insights, member navigation, provider networks, and robust claims management. By connecting various stakeholders in the healthcare ecosystem, Vālenz aims to improve health outcomes and streamline the healthcare experience for all involved.
Bill Review • Out-of-Network Repricing • Primary PPO and Alternative Repricing Administration • EDI and Clearinghouse Solutions • Medical Management
Data Engineer II
March 9
Vālenz® Health
Vālenz® Health is a comprehensive health plan solutions provider that offers a fully integrated platform designed to simplify the complexities of healthcare for employers, payers, providers, and members. The company focuses on enhancing quality and lowering costs through data-driven insights, member navigation, provider networks, and robust claims management. By connecting various stakeholders in the healthcare ecosystem, Vālenz aims to improve health outcomes and streamline the healthcare experience for all involved.
Bill Review • Out-of-Network Repricing • Primary PPO and Alternative Repricing Administration • EDI and Clearinghouse Solutions • Medical Management
📋 Description
• As a Data Engineer II, you’ll design and maintain high-performance data pipelines, automate processes, and implement scalable data storage solutions using Databricks on Azure • Drive continuous improvement initiatives to enhance data processing capabilities across the organization • Design and implement efficient, high-performance data ingestion pipelines from diverse sources utilizing Databricks on Azure • Develop and maintain reliable data pipelines, automating manual processes to improve efficiency and scalability • Collaborate with the Data Engineering team to design and support robust processes for loading data into relational, dimensional, and NoSQL database systems • Implement best practices in data lake architecture to ensure scalable, standardized, and optimized data storage and processing solutions • Partner with cross-functional teams to identify, evaluate, and acquire new data sources that align with organizational objectives • Actively participate in agile development processes, contributing to sprint planning, refinement, and delivery of high-quality solutions • Reasonable accommodation may be made to enable individuals with disabilities to perform essential duties
🎯 Requirements
• 4+ years experience in a highly technical and hands-on data engineering, or data science role • Proficiency with Databricks and/or PySpark is a strong advantage • Hands-on experience in developing ETL processes • Familiarity with Data Lakehouse systems and/or migrating RDBMS to Lakehouse architectures • Strong organizational and time management skills to manage multiple projects with minimal supervision • Ability to build and refine processes from the ground up • Excellent problem-solving skills, with a keen ability to investigate beyond initial findings • Exceptional attention to detail, with a commitment to testing and validating results • Comfortable working with unstructured data and navigating ambiguous outcomes • A plus if you have: Bachelor’s degree in a quantitative field such as statistics, mathematics, engineering, or computer science • Knowledge of common healthcare data types (e.g., medical claims, eligibility, provider networks, Rx claims) from various sources • Python or Databricks certifications
🏖️ Benefits
• Competitive benefits package with generous employer subsidies • Flexible and remote working options • 401k with generous employer match and immediate vesting • Personal and professional development opportunities • Supportive family benefits, including paid leave for new family members • Companywide philanthropic program, Valenz Communities Connection
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🇺🇸 United States – Remote
💰 Post-IPO Debt on 2023-08
⏰ Full Time
🟡 Mid-level
🟠 Senior
🚰 Data Engineer
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