Senior Data Engineer

About the RoleWe are seeking an experienced and strategic Director of Data Engineering to lead theHealth Onboarding Automation team. This role will provide technical and organizationalleadership for software and data solutions that automate, scale, and improve onboardingworkflows within our client’s health program.The Director will partner closely with a project delivery team, product leadership,architecture, information security, DevOps, data engineering, and other software teamsacross the health program. This leader will be responsible for aligning engineering executionwith business priorities, ensuring delivery excellence, and advancing modern software, data,and AI capabilities that support secure and compliant health records management.The ideal candidate is a hands-on strategic leader with deep experience delivering complexSaaS and cloud-native platforms, strong knowledge of health records management, ETLprocessing, and data governance, and practical experience with data engineering in AWS,including AWS Glue. This role also requires the ability to guide the responsible use of AImodels to improve automation, data extraction, classification, workflow intelligence, andoperational efficiency.Key ResponsibilitiesLead, mentor, and develop high-performing engineering teams responsible for HealthOnboarding Automation software and data capabilities.Own the engineering strategy, execution roadmap, and delivery outcomes for automation solutions supporting health records onboarding and related workflows.Partner with project delivery teams and other software teams in the health program to coordinate architecture, dependencies, integration patterns, release planning, and execution.Provide technical leadership across SaaS software engineering, cloud-native architecture, data pipelines, health records management, and applied AI model usage.Oversee the full software development lifecycle, from discovery and design through development, testing, deployment, monitoring, and continuous improvement.Drive delivery of scalable, secure, and maintainable solutions that support health records ingestion, transformation, indexing, classification, validation, and onboarding automation.Lead data engineering initiatives using AWS services, especially AWS Glue, to support automated data processing, ETL/ELT workflows, data quality, and integration with downstream systems.Guide the use of AI and machine learning models to support intelligent automation, including document understanding, metadata extraction, classification, matching, validation, and workflow decision support.Ensure solutions are designed with appropriate attention to security, privacy, compliance, auditability, records retention, and health information governance.Collaborate with Product, Architecture, Information Security, DevOps, QA, DataEngineering, and Operations stakeholders to ensure solutions deliver measurable business value.Establish and improve engineering practices, SDLC standards, Agile delivery processes, technical governance, quality controls, and operational readiness.Monitor portfolio health, risks, dependencies, delivery metrics, and technical debt; proactively escalate and resolve issues that may impact delivery or business outcomes.Support talent development through hiring, coaching, performance management, succession planning, and the creation of a strong engineering culture.Represent the Health Onboarding Automation engineering function in leadership forums, providing clear updates on delivery performance, risks, opportunities, and strategic needs.Stay current with emerging trends in healthcare technology, records management, cloud data engineering, AI-enabled automation, SaaS architecture, and software delivery practices.Required Skills & Experience10+ years of software engineering experience, including at least 5 years in senior engineering leadership roles.Proven experience leading high-performing software engineering teams delivering complex SaaS, cloud-native, or enterprise software platforms.Experience managing the full software development lifecycle and delivering projects on time, within scope, and aligned to business objectives.Strong technical foundation in modern software engineering principles, architecture, API design, integration patterns, cloud platforms, DevOps practices, and operational excellence.Experience with health records management, health information workflows, records ingestion, data governance, retention, privacy, or adjacent healthcare technology domains.Strong data engineering experience, including ETL/ELT pipeline design, data quality management, data transformation, and scalable cloud-based data processing.Practical experience with AWS data services, especially AWS Glue; experience with related AWS services such as S3, Lambda, Step Functions, CloudWatch, IAM, Athena, and Redshift is preferred. Experience with AI services such as Amazon Bedrock or similar model integration platforms is a strong plus.Experience guiding the use of AI models in production or enterprise workflows, including model integration, prompt/model evaluation, responsible AI practices, data privacy, and human-in-the-loop review patterns.Experience partnering with product management, architecture, DevOps, information security, QA, operations, and senior business stakeholders.Strong understanding of Agile delivery practices, engineering governance, risk management, dependency management, and continuous improvement.Excellent leadership, communication, stakeholder management, and decision-making skills.Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Data Engineering, or a related field, or equivalent professional experience.Preferred QualificationsExperience in healthcare, health information management, medical records, release of information, clinical document workflows, or regulated records environments. HL7 FHIR is a strong plus.Experience designing automation for document onboarding, classification, indexing, extraction, validation, or workflow orchestration.Experience with Java, Spring Boot, REST APIs, React or Angular, microservices, containers, Kubernetes, and modern CI/CD practices.Experience with cloud-native composite architectures and enterprise SaaS platforms.Experience applying AI/ML, OCR, NLP, large language models, or intelligent document processing to business workflows.Familiarity with compliance expectations related to sensitive health information, privacy, security, auditability, and records lifecycle management.Experience leading distributed or remote teams across multiple functional domains.Core CompetenciesEngineering Leadership & Talent DevelopmentHealth Records Management & Information GovernanceData Engineering & AWS GlueAI-Enabled AutomationSaaS & Cloud-Native ArchitectureAgile Delivery & SDLC GovernanceCross-Functional CollaborationStrategic Planning & ExecutionRisk Management & Delivery AssuranceStakeholder CommunicationSecurity, Privacy & Compliance MindsetContinuous Improvement & Operational Excellence