[Remote] Sr. Engineer, Data - Archimedes

Note: The job is a remote job and is open to candidates in USA. Navitus Health Solutions is a leader in specialty drug management solutions, aiming to transform the PBM industry. The Sr. Engineer, Data is responsible for leading enterprise data engineering and architecture initiatives, focusing on modernizing data platforms and ensuring data governance to support analytics and AI initiatives.ResponsibilitiesServe as the technical lead for enterprise data engineering, lakehouse architecture, data modeling, and data platform modernization initiativesDesign and implement lake house architectures utilizing Azure Databricks, Delta Lake, Azure Data Lake Storage Gen2, Unity Catalog, and related modern data platform technologiesDevelop canonical enterprise data models, business entity mappings, master data structures, and reusable data products supporting enterprise reporting, analytics, automation, and AI initiativesBuild and maintain bronze, silver, and gold data layers supporting governed, trusted, and AI-ready datasetsDevelop and maintain metadata, data dictionaries, business glossaries, lineage documentation, and data catalog integrations supporting enterprise data governanceDesign, develop, and maintain ETL pipelines for structured and unstructured data across cloud and on-prem environmentsBuild and optimize data models, schemas, and storage solutions in SQL Server, PostgreSQL, and cloud-native databasesDesign and deliver AI-ready data products supporting machine learning, generative AI, intelligent automation, retrieval-augmented generation (RAG), and agent-based AI solutionsSupport feature engineering, vectorization pipelines, document enrichment, semantic search, and knowledge management capabilities used by enterprise AI platformsDesign and support healthcare data integration patterns including claims, eligibility, pharmacy, clinical, operational, financial, and third-party partner dataDefine and maintain enterprise data architecture standards, canonical data models, integration patterns, naming conventions, and data governance frameworksLead enterprise data modeling efforts across operational, analytical, and AI workloads, ensuring consistent business definitions and semantic alignment across platformsEstablish and govern enterprise data dictionaries, business glossaries, metadata standards, data lineage frameworks, and data stewardship practicesProvide technical leadership and mentorship to Data Engineers, Data Integration Engineers, Analytics Engineers, and related technical resourcesConduct architecture reviews for data platforms, integrations, analytics solutions, AI initiatives, and modernization programsDesign enterprise data products and reusable domain-oriented datasets supporting reporting, analytics, automation, machine learning, and generative AI use casesDefine reference architectures for healthcare data integration, interoperability, operational reporting, AI-ready datasets, and governed analytical platformsSupport ingestion and transformation of structured, semi-structured, and unstructured healthcare datasets from internal and external sourcesImplement CI/CD workflows for data pipeline deployment and monitoring using tools such as GitHub Actions, Azure DevOps, or JenkinsDevelop and maintain data integrations using AWS Glue, Azure Data Factory, Lambda, EventBridge, and other cloud-native servicesDesign and implement DataOps practices including automated testing, deployment automation, data quality validation, monitoring, observability, and CI/CD pipelines for data workloadsDevelop API-based integrations supporting SaaS platforms, operational applications, third-party systems, healthcare data exchanges, intelligent automation platforms, and enterprise workflowsDesign and support event-driven architectures utilizing Event Hub, Event Grid, Service Bus, APIs, webhooks, and streaming data technologiesSupport machine learning, artificial intelligence, predictive analytics, and intelligent automation initiatives by developing scalable data pipelines, feature engineering datasets, training datasets, and operationalized data productsPartner with RPA, automation, analytics, and AI teams to support workflow automation, intelligent document processing, agent-based AI solutions, and enterprise automation initiativesImplement secure data engineering practices including encryption, RBAC, data masking, row-level security, auditing, lineage tracking, and governance controlsEnsure data quality, lineage, and governance through automated validation, logging, and monitoring frameworksCollaborate with cross-functional teams to gather requirements, design scalable solutions, and support analytics and reporting needsMonitor and troubleshoot data pipeline performance, latency, and failures; implement proactive alerting and remediation strategiesSupport data security and compliance by enforcing access controls, encryption standards, and audit logging aligned with HIPAA and SOC 2Maintain documentation for data flows, architecture diagrams, and operational proceduresParticipate in sprint planning, code reviews, and agile ceremonies to support iterative development and continuous improvementEvaluate and integrate new data tools, frameworks, and cloud services to enhance platform capabilitiesPartner with DevOps and Security teams to ensure infrastructure-as-code and secure deployment practices are followedParticipate in, adhere to, and support compliance, people and culture, and learning programsPerform other duties as assignedSkillsBachelor's degree in Computer Science, Information Systems, Data Engineering, or related field requiredAWS Certified Data Analytics or Solutions Architect, Microsoft Certified: Azure Data Engineer Associate, and Certified Data Management Professional (CDMP) required8+ years of experience in Data Engineering, Data Architecture, Analytics Engineering, Data Platform Engineering, or related disciplines required5+ years of experience designing and implementing modern lake house architectures utilizing Azure Databricks, Delta Lake, Azure Data Lake Storage Gen2, Unity Catalog, and related cloud-native data technologies requiredDemonstrated experience leading enterprise data architecture, canonical data modeling, data governance, master data management, and large-scale data modernization initiatives requiredExperience designing enterprise data products, semantic models, business entity mappings, data dictionaries, and governed analytical datasets requiredStrong experience with Apache Spark, PySpark, SQL, Python, DataOps automation, CI/CD pipelines, and cloud-native data engineering practices requiredExperience supporting and modernizing legacy SQL-based ETL, reporting, data warehouse, and operational data environments requiredMaster's degree preferredExperience supporting machine learning, AI, generative AI, intelligent automation, retrieval-augmented generation (RAG), vector-based architectures, and AI-ready data platforms preferredExperience planning and executing migrations from traditional database-centric architectures to cloud-native lakehouse, analytics, and AI platforms preferredExperience rationalizing legacy data assets, consolidating data pipelines, and establishing enterprise data architecture standards preferredExperience supporting healthcare data domains including claims, eligibility, pharmacy, clinical, operational, provider, financial, and regulatory data preferredExperience mentoring engineers, conducting architecture reviews, establishing engineering standards, and providing technical leadership across cross-functional teams preferredKnowledge of modern data architecture patterns including Data Mesh, Data Products, Medallion Architecture, Master Data Management, Event-Driven Architecture, and Lakehouse Governance preferredExperience developing canonical data models, enterprise data products, data mappings, master data structures, and governed analytical datasets preferredExperience building DataOps pipelines, automated testing frameworks, CI/CD processes, and data quality controls preferredExperience supporting AI, machine learning, analytics, automation, and intelligent business solutions through scalable data engineering practices preferredExperience working within regulated environments supporting HIPAA, HITRUST, SOC 2, NIST, or similar compliance frameworks preferredBenefitsTop of the industry benefits for Health, Dental, and Vision insurance4 weeks paid parental leave9 paid holidays401K company match of up to 5% - No vesting requirementAdoption Assistance ProgramFlexible Spending AccountEducational Assistance Plan and Professional Membership assistanceReferral Bonus Program – up to $750!Company OverviewNavitus Health Solutions LLC is a full service, URAC-accredited pharmacy benefit management company. It was founded in 2003, and is headquartered in Appleton, Wisconsin, USA, with a workforce of 1001-5000 employees. Its website is https://www.navitus.com/.