Data Engineer III

🔥 19 minutes ago

🇺🇸 United States – Remote

💵 $94.1k - $164.8k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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CareSource

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 30+ years

🏥 Healthcare

🛡️ Insurance

⚕️ Healthcare Insurance

Healthcare • Insurance • Healthcare Insurance

CareSource is a health services company focused on providing affordable health insurance and healthcare solutions. It offers a wide range of plans including Medicaid, Marketplace, and Medicare Advantage, targeting low-income adults, families, children, pregnant women, elderly adults, and people with disabilities. Additionally, CareSource provides members with resources for COVID-19 support, dental, vision, and hearing benefits, as well as pharmacy services. The company emphasizes easy access to healthcare management through online platforms and a mobile app.

📋 Description

• Design, develop, test, deploy, and support scalable ETL/ELT pipelines, data models, and analytical data assets • Improve data solution performance, reliability, and maintainability throughout the delivery lifecycle • Contribute to data stewardship workgroups and cross-functional data management and governance teams • Promote metadata management and data quality practices through knowledge-sharing and technical guidance • Translate stakeholder priorities, business definitions, and data quality requirements into data models, technical specifications, and engineering solutions • Own technical delivery of assigned data governance engineering initiatives, including metadata cataloging and data quality solutions • Develop and maintain glossary definitions, policies, standards, guidelines, and workflows for data management and governance programs • Lead metadata catalogs for assigned data domains, including technical metadata, business definitions, and data lineage • Identify and quantify data issues, assess business impact, and implement remediation plans with stakeholders • Define business rules and implement automated controls to measure and improve data quality • Investigate and resolve data quality issues; report remediation progress, quality trends, and standards adherence • Build and maintain governed, AI-ready datasets and pipelines for AI and machine learning use cases • Integrate and support approved AI capabilities in data engineering workflows, including AI-assisted quality checks, metadata enrichment, and unstructured data processing • Validate AI outputs and monitor accuracy, reliability, latency, and cost • Use approved AI-assisted development tools for coding, testing, troubleshooting, and documentation while protecting sensitive data and following security, privacy, and responsible AI requirements • Manage technical delivery, dependencies, risks, and operational goals independently • Resolve ambiguous, non-routine technical problems and escalate decisions outside established boundaries • Perform other duties as requested

🎯 Requirements

• Bachelor’s degree in Computer Science or a related field, or equivalent years of relevant work experience, required • Minimum of five (5) years of experience designing and developing ETL/ELT and/or business intelligence solutions • Experience across requirements definition, design, implementation, testing, deployment, and production support of complex database, data integration, business intelligence, and analytical solutions • Hands-on experience independently implementing and supporting AI-enabled data engineering solutions in a production environment • Experience preparing and governing data, integrating AI services or models into data workflows, validating outputs, and monitoring operational performance • Advanced SQL skills, including complex query development, troubleshooting, and performance optimization • Proficiency in Python or a comparable programming language • Experience developing data profiling, data quality, and metadata analysis processes using industry-standard tools • Ability to manage technical deliverables across multiple medium- to large-scale projects • Strong understanding of data management and governance, data quality, metadata management, lineage, stewardship, and access controls • Strong understanding of relational database theory, data modeling, and data warehouse design principles • Working knowledge of AI and machine learning data requirements and practical AI integration patterns, including model inference APIs and, where applicable, embeddings and retrieval-augmented generation (RAG) • Ability to evaluate AI-enabled workflows using representative test data and defined quality measures • Proficiency with version control, code review, automated testing, deployment practices, and operational monitoring • Healthcare payer experience preferred • Experience within a formal data warehouse and data governance environment preferred

🏖️ Benefits

• Bonus tied to company and individual performance may be available • Substantial and comprehensive total rewards package • Total well-being support

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