Vālenz® Health is the platform to simplify healthcare – the destination for employers, payers, providers and members to reduce costs, improve quality, and elevate the healthcare experience. The Valenz mindset and culture of innovation combine to create a distinctly different approach to an inefficient, uninspired health system. With fully integrated solutions, Valenz engages early and often to execute across the entire patient journey – from care navigation and management to payment integrity, plan performance and provider verification. With a 99% client retention rate, we elevate expectations to a new level of efficiency, effectiveness and transparency where smarter, better, faster healthcare is possible. About This Opportunity: As a Data Engineer III, you’ll be responsible for designing, building, and evolving scalable data systems that power analytics, product, and operational decision-making across the organization. You will operate as a senior individual contributor with end-to-end ownership of complex data initiatives, contributing directly to the architecture and evolution of our Databricks-based Lakehouse platform on Azure. Things You’ll Do Here: - Own the design and implementation of scalable, production-grade data pipelines using Databricks, PySpark, SQL, and Python Operationalize machine learning workflows and feature pipelines. - Own and deliver complex, cross-functional data initiatives end-to-end, from ingestion and data modeling through production deployment and ongoing monitoring. - Design robust, reusable ETL frameworks using Delta Lake best practices (incremental processing, merge/upserts, schema evolution). - Diagnose and resolve performance challenges in distributed Spark workloads (data skew, shuffle, memory pressure, inefficient execution plans). - Build and enforce strong data quality practices, including validation frameworks, observability, and automated alerting. - Design and evolve data models across medallion architecture layers to support analytics and downstream applications. - Implement modern data ingestion patterns, including API-driven, event-based, and AI-assisted ingestion workflows. - Partner with analytics, architecture, and engineering teams to support advanced data use cases, including feature engineering and emerging machine learning workflows. - Evaluate and adopt new capabilities within Azure and Databricks (e.g., MLflow, Unity Catalog enhancements, platform optimizations) to improve scalability and developer productivity. - Contribute to architectural decisions and platform standards, balancing short-term delivery with long-term maintainability. - Write high-quality, well-tested, and maintainable code; lead by example through thoughtful code reviews. - Act as a go-to resource for diagnosing and resolving complex production issues across systems. - Mentor and elevate other engineers through collaboration, design discussions, and technical guidance. - 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: - 4+ years of experience in data engineering or a related field, with a track record of delivering production-grade data systems - Strong hands-on experience with Databricks, Spark/PySpark, and distributed data processing at scale - Deep understanding of Delta Lake and modern Lakehouse architecture patterns - Proficiency in Python and SQL for large-scale data transformation and performance optimization - Proven experience building incremental, idempotent, and highly reliable data pipelines - Strong experience diagnosing and optimizing Spark workloads (partitioning strategies, AQE, caching, file sizing, query tuning) - Experience designing data models for analytics and downstream consumption (medallion architecture, dimensional modeling, or similar) - Experience implementing data quality, validation, and observability frameworks in production environments - Familiarity with CI/CD, version control, and modern DataOps practices - Experience supporting or integrating with machine learning workflows (feature pipelines, model inputs/outputs, or ML lifecycle support) - Familiarity with AI/ML concepts as applied to data engineering (intelligent ingestion, anomaly detection, automation) - Demonstrated ability to evaluate and adopt new technologies within cloud ecosystems (Azure, Databricks) - Strong communication skills and ability to collaborate with both technical and non-technical stakeholders A plus if you have… - Familiarity with event-driven architectures (e.g., streaming, message queues, or event hubs) - Experience working with healthcare data (claims, eligibility, provider, or clinical datasets Where You’ll Work: This is a fully remote position, and we’ll provide all the necessary equipment! - Work Environment: You’ll need a quiet workspace that is free from distractions. - Technology: Reliable internet connection—if you can use streaming services, you’re good to go! - Security: Adherence to company security protocols, including the use of VPNs, secure passwords, and company-approved devices/software. - Location: You must be US based, in a location where you can work effectively and comply with company policies such as HIPAA. Why You'll Love Working Here Valenz is proud to be recognized by Inc. 5000 as one of America’s fastest-growing private companies. Our team is committed to delivering on our promise to engage early and often for smarter, better, faster healthcare. With this commitment, you’ll find an engaged culture – one that stands strong, vigorous, and healthy in all we do. Benefits - Generously subsidized company-sponsored Medical, Dental, and Vision insurance, with access to services through our own products, Healthcare Blue Book and KISx Card. - Spending account options: HSA, FSA, and DCFSA - 401K with company match and immediate vesting - Flexible working environment - Generous Paid Time Off to include vacation, sick leave, and paid holidays - Employee Assistance Program that includes professional counseling, referrals, and additional services - Paid maternity and paternity leave - Pet insurance - Employee discounts on phone plans, car rentals and computers - Community giveback opportunities, including paid time off for philanthropic endeavors At Valenz, we celebrate, support, and thrive on inclusion, for the benefit of our associates, our partners, and our products. Valenz is committed to the principle of equal employment opportunity for all associates and to providing associates with a work environment free of discrimination and harassment. All employment decisions at Valenz are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, national, social, or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. We will not tolerate discrimination or harassment based on any of these characteristics.

• Build and scale high-throughput streaming pipelines. Design, implement, and operate pipelines ingesting 400M+ monthly MLS updates across 350+ integrations using Airflow, Spark Streaming, Kafka, and Iceberg—ensuring reliability, performance, and data correctness. • Model and deliver high-quality, production-grade real estate datasets. Develop and maintain datasets that power core product experiences, with a focus on data modeling, transformation logic, and balancing freshness, accuracy, and cost. • Strengthen data quality and observability. Implement and improve data quality checks, monitoring, and alerting to detect issues early and reduce downstream impact. • Leverage AI to improve data operations. Contribute to AI-driven tooling that helps triage, debug, and resolve data quality issues, increasing team efficiency and reducing manual intervention.

• Build and scale high-throughput streaming pipelines. Design, implement, and operate pipelines ingesting 400M+ monthly MLS updates across 350+ integrations using Airflow, Spark Streaming, Kafka, and Iceberg—ensuring reliability, performance, and data correctness. • Model and deliver high-quality, production-grade real estate datasets. Develop and maintain datasets that power core product experiences, with a focus on data modeling, transformation logic, and balancing freshness, accuracy, and cost. • Strengthen data quality and observability. Implement and improve data quality checks, monitoring, and alerting to detect issues early and reduce downstream impact. • Leverage AI to improve data operations. Contribute to AI-driven tooling that helps triage, debug, and resolve data quality issues, increasing team efficiency and reducing manual intervention.

• develop scalable data architectures and take responsibility for business-critical pipelines • actively shape how data is used across the company • design, implement, and optimize high-performance data pipelines • strategically evolve our data architecture and ensure scalability and maintainability • act as an interface and work closely with business units and other affiliated companies • take technical ownership of our data landscape • evaluate and selectively implement new technologies